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4020 4021 4022 4023 4024 4025 4026 4027 4028 4029 4030 4031 4032 4033 4034 4035 4036 4037 4038 4039 4040 4041 4042 4043 4044 4045 4046 4047 4048 4049 4050 4051 4052 4053 4054 4055 4056 4057 4058 4059 4060 4061 4062 | 2020-06-11 20:32:12,836 - crisis_transformers.trainer - INFO - Use pytorch device: cuda, with gpu_number=2
2020-06-11 20:32:14,855 - crisis_transformers.trainer - INFO - Warmup-steps: 55716
2020-06-11 20:32:14,856 - crisis_transformers.trainer - INFO - ***** Running training *****
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Num of training examples (actually iterations per epoch for Iterable Dataset) = 69642
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Steps per Epoch = 17411 or iterations per epoch = 17411
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Num of Epochs = 16
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Best score (perplexity) = -inf
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Eval every 400 steps or every 400 iterations
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Early stop = 20
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Total optimization steps = 278576
2020-06-11 20:32:14,857 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 20:39:27,466 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=400
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Best score (perplexity) = -96754087231488.0
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 13s
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Steps = 400/278576
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - dev_loss = 32.203194 || dev_eval_scores = {'perplexity': 96754087231488.0}
2020-06-11 20:39:28,626 - crisis_transformers.trainer - INFO - train_loss = 34.87022018432617
2020-06-11 20:39:28,627 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 20:46:40,538 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=800
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Best score (perplexity) = -11848.5537109375
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 20:46:44,659 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 20:46:44,660 - crisis_transformers.trainer - INFO - Steps = 800/278576
2020-06-11 20:46:44,660 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 20:46:44,660 - crisis_transformers.trainer - INFO - dev_loss = 9.379961 || dev_eval_scores = {'perplexity': 11848.5537109375}
2020-06-11 20:46:44,660 - crisis_transformers.trainer - INFO - train_loss = 22.25151824951172
2020-06-11 20:46:44,660 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 20:53:56,085 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=1200
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Best score (perplexity) = -82.30923461914062
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Steps = 1200/278576
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 20:53:59,828 - crisis_transformers.trainer - INFO - dev_loss = 4.410483 || dev_eval_scores = {'perplexity': 82.30923461914062}
2020-06-11 20:53:59,829 - crisis_transformers.trainer - INFO - train_loss = 15.844202995300293
2020-06-11 20:53:59,829 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Best score (perplexity) = -82.30923461914062
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:01:11,585 - crisis_transformers.trainer - INFO - Steps = 1600/278576
2020-06-11 21:01:11,586 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:01:11,586 - crisis_transformers.trainer - INFO - dev_loss = 4.528600 || dev_eval_scores = {'perplexity': 92.62876892089844}
2020-06-11 21:01:11,586 - crisis_transformers.trainer - INFO - train_loss = 12.387160301208496
2020-06-11 21:01:11,586 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:08:22,662 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:08:26,396 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=2000
2020-06-11 21:08:26,396 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Best score (perplexity) = -13.568625450134277
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Steps = 2000/278576
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - dev_loss = 2.607760 || dev_eval_scores = {'perplexity': 13.568625450134277}
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO - train_loss = 10.256034851074219
2020-06-11 21:08:26,397 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:15:38,560 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:15:42,293 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=2400
2020-06-11 21:15:42,293 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:15:42,293 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Best score (perplexity) = -8.842060089111328
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Steps = 2400/278576
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - dev_loss = 2.179520 || dev_eval_scores = {'perplexity': 8.842060089111328}
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO - train_loss = 8.810672760009766
2020-06-11 21:15:42,294 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:22:54,836 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=2800
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Best score (perplexity) = -6.2656636238098145
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Steps = 2800/278576
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - dev_loss = 1.835085 || dev_eval_scores = {'perplexity': 6.2656636238098145}
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO - train_loss = 7.770569324493408
2020-06-11 21:22:58,961 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:30:11,274 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:30:11,274 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Best score (perplexity) = -6.2656636238098145
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Steps = 3200/278576
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - dev_loss = 1.864289 || dev_eval_scores = {'perplexity': 6.451348781585693}
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO - train_loss = 6.985172748565674
2020-06-11 21:30:11,275 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:37:22,915 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=3600
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Best score (perplexity) = -4.507174015045166
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Steps = 3600/278576
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:37:27,050 - crisis_transformers.trainer - INFO - dev_loss = 1.505670 || dev_eval_scores = {'perplexity': 4.507174015045166}
2020-06-11 21:37:27,051 - crisis_transformers.trainer - INFO - train_loss = 6.368422985076904
2020-06-11 21:37:27,051 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:44:38,761 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=4000
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Best score (perplexity) = -4.046299457550049
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Steps = 4000/278576
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - dev_loss = 1.397803 || dev_eval_scores = {'perplexity': 4.046299457550049}
2020-06-11 21:44:42,509 - crisis_transformers.trainer - INFO - train_loss = 5.87202262878418
2020-06-11 21:44:42,510 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:51:54,477 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:51:58,342 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=4400
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.7213120460510254
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Steps = 4400/278576
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - dev_loss = 1.314076 || dev_eval_scores = {'perplexity': 3.7213120460510254}
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO - train_loss = 5.462299346923828
2020-06-11 21:51:58,343 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 21:59:10,274 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=4800
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.609790325164795
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Steps = 4800/278576
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 21:59:14,545 - crisis_transformers.trainer - INFO - dev_loss = 1.283650 || dev_eval_scores = {'perplexity': 3.609790325164795}
2020-06-11 21:59:14,546 - crisis_transformers.trainer - INFO - train_loss = 5.118622303009033
2020-06-11 21:59:14,546 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:06:26,200 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=5200
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.5901994705200195
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Steps = 5200/278576
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:06:29,929 - crisis_transformers.trainer - INFO - dev_loss = 1.278208 || dev_eval_scores = {'perplexity': 3.5901994705200195}
2020-06-11 22:06:29,930 - crisis_transformers.trainer - INFO - train_loss = 4.828340530395508
2020-06-11 22:06:29,930 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:13:41,909 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=5600
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.394659996032715
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Steps = 5600/278576
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:13:46,201 - crisis_transformers.trainer - INFO - dev_loss = 1.222204 || dev_eval_scores = {'perplexity': 3.394659996032715}
2020-06-11 22:13:46,202 - crisis_transformers.trainer - INFO - train_loss = 4.5767903327941895
2020-06-11 22:13:46,202 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.394659996032715
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:20:57,774 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-11 22:20:57,775 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:20:57,775 - crisis_transformers.trainer - INFO - Steps = 6000/278576
2020-06-11 22:20:57,775 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:20:57,775 - crisis_transformers.trainer - INFO - dev_loss = 1.227896 || dev_eval_scores = {'perplexity': 3.41403865814209}
2020-06-11 22:20:57,775 - crisis_transformers.trainer - INFO - train_loss = 4.356290340423584
2020-06-11 22:20:57,775 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:28:09,137 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:28:13,001 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=6400
2020-06-11 22:28:13,001 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.263387680053711
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Steps = 6400/278576
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - dev_loss = 1.182766 || dev_eval_scores = {'perplexity': 3.263387680053711}
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO - train_loss = 4.162957668304443
2020-06-11 22:28:13,002 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.263387680053711
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:35:25,098 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO - Steps = 6800/278576
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO - dev_loss = 1.188739 || dev_eval_scores = {'perplexity': 3.2829389572143555}
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO - train_loss = 3.991642713546753
2020-06-11 22:35:25,099 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:42:37,188 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=7200
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.1454687118530273
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 22:42:41,101 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:42:41,102 - crisis_transformers.trainer - INFO - Steps = 7200/278576
2020-06-11 22:42:41,102 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:42:41,102 - crisis_transformers.trainer - INFO - dev_loss = 1.145963 || dev_eval_scores = {'perplexity': 3.1454687118530273}
2020-06-11 22:42:41,102 - crisis_transformers.trainer - INFO - train_loss = 3.8384640216827393
2020-06-11 22:42:41,102 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:49:53,052 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=7600
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.0853919982910156
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Steps = 7600/278576
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:49:56,891 - crisis_transformers.trainer - INFO - dev_loss = 1.126679 || dev_eval_scores = {'perplexity': 3.0853919982910156}
2020-06-11 22:49:56,892 - crisis_transformers.trainer - INFO - train_loss = 3.701063871383667
2020-06-11 22:49:56,892 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 22:57:08,463 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:57:12,524 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=8000
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Best score (perplexity) = -3.04101824760437
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Steps = 8000/278576
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - dev_loss = 1.112192 || dev_eval_scores = {'perplexity': 3.04101824760437}
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO - train_loss = 3.575878143310547
2020-06-11 22:57:12,525 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:04:23,771 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=8400
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.996488571166992
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Steps = 8400/278576
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:04:27,583 - crisis_transformers.trainer - INFO - dev_loss = 1.097441 || dev_eval_scores = {'perplexity': 2.996488571166992}
2020-06-11 23:04:27,584 - crisis_transformers.trainer - INFO - train_loss = 3.4622840881347656
2020-06-11 23:04:27,584 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:11:39,153 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:11:43,019 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=8800
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.9609262943267822
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Steps = 8800/278576
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - dev_loss = 1.085502 || dev_eval_scores = {'perplexity': 2.9609262943267822}
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO - train_loss = 3.3580634593963623
2020-06-11 23:11:43,020 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:18:54,591 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:18:58,463 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=9200
2020-06-11 23:18:58,463 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:18:58,463 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:18:58,463 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.9230592250823975
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Steps = 9200/278576
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - dev_loss = 1.072631 || dev_eval_scores = {'perplexity': 2.9230592250823975}
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO - train_loss = 3.2615966796875
2020-06-11 23:18:58,464 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:26:10,441 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=9600
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.886868715286255
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:26:13,940 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 23:26:13,941 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:26:13,941 - crisis_transformers.trainer - INFO - Steps = 9600/278576
2020-06-11 23:26:13,941 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:26:13,941 - crisis_transformers.trainer - INFO - dev_loss = 1.060172 || dev_eval_scores = {'perplexity': 2.886868715286255}
2020-06-11 23:26:13,941 - crisis_transformers.trainer - INFO - train_loss = 3.1728854179382324
2020-06-11 23:26:13,941 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:33:25,705 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=10000
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.836120128631592
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:33:30,017 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 23:33:30,018 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:33:30,018 - crisis_transformers.trainer - INFO - Steps = 10000/278576
2020-06-11 23:33:30,018 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:33:30,018 - crisis_transformers.trainer - INFO - dev_loss = 1.042437 || dev_eval_scores = {'perplexity': 2.836120128631592}
2020-06-11 23:33:30,018 - crisis_transformers.trainer - INFO - train_loss = 3.091641664505005
2020-06-11 23:33:30,018 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:40:41,837 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=10400
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.8059732913970947
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:40:45,836 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO - Steps = 10400/278576
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO - dev_loss = 1.031750 || dev_eval_scores = {'perplexity': 2.8059732913970947}
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO - train_loss = 3.0152587890625
2020-06-11 23:40:45,837 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:47:57,612 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=10800
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.772104263305664
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Steps = 10800/278576
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:48:02,018 - crisis_transformers.trainer - INFO - dev_loss = 1.019607 || dev_eval_scores = {'perplexity': 2.772104263305664}
2020-06-11 23:48:02,019 - crisis_transformers.trainer - INFO - train_loss = 2.9444949626922607
2020-06-11 23:48:02,019 - crisis_transformers.trainer - INFO -
********************************************
2020-06-11 23:55:13,323 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=11200
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.7492218017578125
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Steps = 11200/278576
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - dev_loss = 1.011318 || dev_eval_scores = {'perplexity': 2.7492218017578125}
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO - train_loss = 2.8781516551971436
2020-06-11 23:55:17,272 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:02:29,325 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=11600
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.7139976024627686
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:02:33,443 - crisis_transformers.trainer - INFO - Steps = 11600/278576
2020-06-12 00:02:33,444 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:02:33,444 - crisis_transformers.trainer - INFO - dev_loss = 0.998423 || dev_eval_scores = {'perplexity': 2.7139976024627686}
2020-06-12 00:02:33,444 - crisis_transformers.trainer - INFO - train_loss = 2.816199541091919
2020-06-12 00:02:33,444 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:09:45,484 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=12000
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.68788480758667
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Steps = 12000/278576
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:09:49,444 - crisis_transformers.trainer - INFO - dev_loss = 0.988755 || dev_eval_scores = {'perplexity': 2.68788480758667}
2020-06-12 00:09:49,445 - crisis_transformers.trainer - INFO - train_loss = 2.7574315071105957
2020-06-12 00:09:49,445 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:17:00,535 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=12400
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.654526710510254
2020-06-12 00:17:04,295 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - Steps = 12400/278576
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - dev_loss = 0.976266 || dev_eval_scores = {'perplexity': 2.654526710510254}
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO - train_loss = 2.7026596069335938
2020-06-12 00:17:04,296 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:24:16,075 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=12800
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.6282081604003906
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 00:24:19,961 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:24:19,962 - crisis_transformers.trainer - INFO - Steps = 12800/278576
2020-06-12 00:24:19,962 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:24:19,962 - crisis_transformers.trainer - INFO - dev_loss = 0.966302 || dev_eval_scores = {'perplexity': 2.6282081604003906}
2020-06-12 00:24:19,962 - crisis_transformers.trainer - INFO - train_loss = 2.650250196456909
2020-06-12 00:24:19,962 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:31:31,505 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=13200
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.6085095405578613
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Steps = 13200/278576
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - dev_loss = 0.958779 || dev_eval_scores = {'perplexity': 2.6085095405578613}
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO - train_loss = 2.600867986679077
2020-06-12 00:31:35,203 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:38:46,576 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:38:50,406 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=13600
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.572343587875366
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Steps = 13600/278576
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - dev_loss = 0.944817 || dev_eval_scores = {'perplexity': 2.572343587875366}
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO - train_loss = 2.55434513092041
2020-06-12 00:38:50,407 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:46:01,097 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=14000
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.5420730113983154
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Steps = 14000/278576
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - dev_loss = 0.932980 || dev_eval_scores = {'perplexity': 2.5420730113983154}
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO - train_loss = 2.509788751602173
2020-06-12 00:46:05,257 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 00:53:16,943 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:53:20,794 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=14400
2020-06-12 00:53:20,794 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 00:53:20,794 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 00:53:20,794 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 00:53:20,794 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.508371114730835
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Steps = 14400/278576
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - dev_loss = 0.919634 || dev_eval_scores = {'perplexity': 2.508371114730835}
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO - train_loss = 2.4678986072540283
2020-06-12 00:53:20,795 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:00:31,540 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=14800
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.4876623153686523
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Steps = 14800/278576
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - dev_loss = 0.911343 || dev_eval_scores = {'perplexity': 2.4876623153686523}
2020-06-12 01:00:35,779 - crisis_transformers.trainer - INFO - train_loss = 2.428267002105713
2020-06-12 01:00:35,780 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:07:47,187 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:07:51,019 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=15200
2020-06-12 01:07:51,019 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:07:51,019 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:07:51,019 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:07:51,019 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:07:51,019 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.46309757232666
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Steps = 15200/278576
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - dev_loss = 0.901420 || dev_eval_scores = {'perplexity': 2.46309757232666}
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO - train_loss = 2.3902571201324463
2020-06-12 01:07:51,020 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:15:02,762 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=15600
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.4311938285827637
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:15:06,595 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO - Steps = 15600/278576
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO - dev_loss = 0.888382 || dev_eval_scores = {'perplexity': 2.4311938285827637}
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO - train_loss = 2.354424238204956
2020-06-12 01:15:06,596 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:22:18,392 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=16000
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.4099924564361572
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:22:22,372 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO - Steps = 16000/278576
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO - dev_loss = 0.879624 || dev_eval_scores = {'perplexity': 2.4099924564361572}
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO - train_loss = 2.319091796875
2020-06-12 01:22:22,373 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:29:33,829 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:29:37,786 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=16400
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.3866090774536133
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Steps = 16400/278576
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - dev_loss = 0.869874 || dev_eval_scores = {'perplexity': 2.3866090774536133}
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO - train_loss = 2.285768747329712
2020-06-12 01:29:37,787 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:36:48,893 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=16800
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.3575546741485596
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Steps = 16800/278576
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - dev_loss = 0.857625 || dev_eval_scores = {'perplexity': 2.3575546741485596}
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO - train_loss = 2.253655433654785
2020-06-12 01:36:52,733 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:44:04,158 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Save check-point at epoch=0 step=17200
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.3273518085479736
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Epoch = 1/16
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Steps = 17200/278576
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:44:08,000 - crisis_transformers.trainer - INFO - dev_loss = 0.844731 || dev_eval_scores = {'perplexity': 2.3273518085479736}
2020-06-12 01:44:08,001 - crisis_transformers.trainer - INFO - train_loss = 2.22310733795166
2020-06-12 01:44:08,001 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:46:08,626 - crisis_transformers.trainer - INFO - epoch 1 ends, 15 epoches left
2020-06-12 01:46:08,628 - crisis_transformers.trainer - INFO -
global_average_loss=2.207577705383301,global_steps=17411 on training set
2020-06-12 01:51:18,826 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=189
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.306220054626465
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Steps = 17600/278576
2020-06-12 01:51:22,899 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:51:22,900 - crisis_transformers.trainer - INFO - dev_loss = 0.835610 || dev_eval_scores = {'perplexity': 2.306220054626465}
2020-06-12 01:51:22,900 - crisis_transformers.trainer - INFO - train_loss = 0.8919339776039124
2020-06-12 01:51:22,900 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 01:58:34,239 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=589
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.282672166824341
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 01:58:38,515 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - Steps = 18000/278576
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - dev_loss = 0.825347 || dev_eval_scores = {'perplexity': 2.282672166824341}
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO - train_loss = 0.9102271199226379
2020-06-12 01:58:38,516 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:05:49,927 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:05:53,796 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=989
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.261589288711548
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Steps = 18400/278576
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - dev_loss = 0.816068 || dev_eval_scores = {'perplexity': 2.261589288711548}
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO - train_loss = 0.9082818031311035
2020-06-12 02:05:53,797 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:13:04,838 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=1389
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.2358696460723877
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Steps = 18800/278576
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - dev_loss = 0.804630 || dev_eval_scores = {'perplexity': 2.2358696460723877}
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO - train_loss = 0.9062302708625793
2020-06-12 02:13:08,577 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:20:19,901 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=1789
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:20:23,756 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.210675001144409
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Steps = 19200/278576
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - dev_loss = 0.793298 || dev_eval_scores = {'perplexity': 2.210675001144409}
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO - train_loss = 0.8982809782028198
2020-06-12 02:20:23,757 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:27:35,383 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=2189
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.1900641918182373
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Steps = 19600/278576
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:27:39,229 - crisis_transformers.trainer - INFO - dev_loss = 0.783931 || dev_eval_scores = {'perplexity': 2.1900641918182373}
2020-06-12 02:27:39,230 - crisis_transformers.trainer - INFO - train_loss = 0.8898405432701111
2020-06-12 02:27:39,230 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:34:50,458 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=2589
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.169043779373169
2020-06-12 02:34:54,307 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - Steps = 20000/278576
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - dev_loss = 0.774286 || dev_eval_scores = {'perplexity': 2.169043779373169}
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO - train_loss = 0.8851494789123535
2020-06-12 02:34:54,308 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:42:06,145 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=2989
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.140289783477783
2020-06-12 02:42:09,896 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - Steps = 20400/278576
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - dev_loss = 0.760941 || dev_eval_scores = {'perplexity': 2.140289783477783}
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO - train_loss = 0.8793467283248901
2020-06-12 02:42:09,897 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:49:21,789 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=3389
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.121040105819702
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Steps = 20800/278576
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:49:25,274 - crisis_transformers.trainer - INFO - dev_loss = 0.751907 || dev_eval_scores = {'perplexity': 2.121040105819702}
2020-06-12 02:49:25,275 - crisis_transformers.trainer - INFO - train_loss = 0.871684730052948
2020-06-12 02:49:25,275 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 02:56:37,107 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:56:41,332 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=3789
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.0992023944854736
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Steps = 21200/278576
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - dev_loss = 0.741557 || dev_eval_scores = {'perplexity': 2.0992023944854736}
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO - train_loss = 0.8670705556869507
2020-06-12 02:56:41,333 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:03:52,858 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=4189
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.0718014240264893
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:03:56,767 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - Steps = 21600/278576
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - dev_loss = 0.728418 || dev_eval_scores = {'perplexity': 2.0718014240264893}
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO - train_loss = 0.8624909520149231
2020-06-12 03:03:56,768 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:11:08,681 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:11:12,544 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=4589
2020-06-12 03:11:12,544 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:11:12,544 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:11:12,544 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:11:12,544 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:11:12,544 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.0530827045440674
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Steps = 22000/278576
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - dev_loss = 0.719342 || dev_eval_scores = {'perplexity': 2.0530827045440674}
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO - train_loss = 0.8574584126472473
2020-06-12 03:11:12,545 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:18:23,725 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:18:27,499 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=4989
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.0336155891418457
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Steps = 22400/278576
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - dev_loss = 0.709815 || dev_eval_scores = {'perplexity': 2.0336155891418457}
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO - train_loss = 0.8504697680473328
2020-06-12 03:18:27,500 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:25:39,057 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=5389
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Best score (perplexity) = -2.0098047256469727
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Steps = 22800/278576
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - dev_loss = 0.698038 || dev_eval_scores = {'perplexity': 2.0098047256469727}
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO - train_loss = 0.8460281491279602
2020-06-12 03:25:43,393 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:32:54,836 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:32:58,726 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=5789
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.9868273735046387
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Steps = 23200/278576
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - dev_loss = 0.686539 || dev_eval_scores = {'perplexity': 1.9868273735046387}
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO - train_loss = 0.8407670855522156
2020-06-12 03:32:58,727 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:40:09,514 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=6189
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.9708765745162964
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Steps = 23600/278576
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:40:13,425 - crisis_transformers.trainer - INFO - dev_loss = 0.678478 || dev_eval_scores = {'perplexity': 1.9708765745162964}
2020-06-12 03:40:13,426 - crisis_transformers.trainer - INFO - train_loss = 0.8364319205284119
2020-06-12 03:40:13,426 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:47:25,312 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=6589
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.950257420539856
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Steps = 24000/278576
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:47:28,665 - crisis_transformers.trainer - INFO - dev_loss = 0.667961 || dev_eval_scores = {'perplexity': 1.950257420539856}
2020-06-12 03:47:28,666 - crisis_transformers.trainer - INFO - train_loss = 0.8307074308395386
2020-06-12 03:47:28,666 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 03:54:40,261 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:54:44,220 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=6989
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.9251375198364258
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Steps = 24400/278576
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - dev_loss = 0.654997 || dev_eval_scores = {'perplexity': 1.9251375198364258}
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO - train_loss = 0.8253822922706604
2020-06-12 03:54:44,221 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:01:55,402 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:01:59,672 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=7389
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.9091284275054932
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Steps = 24800/278576
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - dev_loss = 0.646647 || dev_eval_scores = {'perplexity': 1.9091284275054932}
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO - train_loss = 0.8205176591873169
2020-06-12 04:01:59,673 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:09:10,549 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=7789
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.8884336948394775
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Steps = 25200/278576
2020-06-12 04:09:14,287 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:09:14,288 - crisis_transformers.trainer - INFO - dev_loss = 0.635748 || dev_eval_scores = {'perplexity': 1.8884336948394775}
2020-06-12 04:09:14,288 - crisis_transformers.trainer - INFO - train_loss = 0.8162734508514404
2020-06-12 04:09:14,288 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:16:26,145 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=8189
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.8698856830596924
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:16:30,187 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO - Steps = 25600/278576
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO - dev_loss = 0.625877 || dev_eval_scores = {'perplexity': 1.8698856830596924}
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO - train_loss = 0.811458170413971
2020-06-12 04:16:30,188 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:23:41,295 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:23:45,346 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=8589
2020-06-12 04:23:45,346 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:23:45,346 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.8487507104873657
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Steps = 26000/278576
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - dev_loss = 0.614510 || dev_eval_scores = {'perplexity': 1.8487507104873657}
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO - train_loss = 0.8066449761390686
2020-06-12 04:23:45,347 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:30:56,930 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=8989
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.8316272497177124
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Steps = 26400/278576
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:31:01,239 - crisis_transformers.trainer - INFO - dev_loss = 0.605205 || dev_eval_scores = {'perplexity': 1.8316272497177124}
2020-06-12 04:31:01,240 - crisis_transformers.trainer - INFO - train_loss = 0.802518904209137
2020-06-12 04:31:01,240 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:38:12,636 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=9389
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.8143984079360962
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Steps = 26800/278576
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:38:16,325 - crisis_transformers.trainer - INFO - dev_loss = 0.595754 || dev_eval_scores = {'perplexity': 1.8143984079360962}
2020-06-12 04:38:16,326 - crisis_transformers.trainer - INFO - train_loss = 0.7970281839370728
2020-06-12 04:38:16,326 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:45:27,487 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:45:31,784 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=9789
2020-06-12 04:45:31,784 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:45:31,784 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:45:31,784 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:45:31,784 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:45:31,784 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.7961244583129883
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Steps = 27200/278576
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - dev_loss = 0.585631 || dev_eval_scores = {'perplexity': 1.7961244583129883}
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO - train_loss = 0.7928464412689209
2020-06-12 04:45:31,785 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:52:42,555 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=10189
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.7843670845031738
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 04:52:46,377 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 04:52:46,378 - crisis_transformers.trainer - INFO - Steps = 27600/278576
2020-06-12 04:52:46,378 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 04:52:46,378 - crisis_transformers.trainer - INFO - dev_loss = 0.579064 || dev_eval_scores = {'perplexity': 1.7843670845031738}
2020-06-12 04:52:46,378 - crisis_transformers.trainer - INFO - train_loss = 0.7886567711830139
2020-06-12 04:52:46,378 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 04:59:57,976 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:00:01,818 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=10589
2020-06-12 05:00:01,818 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:00:01,818 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.764768123626709
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Steps = 28000/278576
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - dev_loss = 0.568019 || dev_eval_scores = {'perplexity': 1.764768123626709}
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO - train_loss = 0.7840659618377686
2020-06-12 05:00:01,819 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:07:12,938 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=10989
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.7483080625534058
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Steps = 28400/278576
2020-06-12 05:07:16,789 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:07:16,790 - crisis_transformers.trainer - INFO - dev_loss = 0.558648 || dev_eval_scores = {'perplexity': 1.7483080625534058}
2020-06-12 05:07:16,790 - crisis_transformers.trainer - INFO - train_loss = 0.7798082828521729
2020-06-12 05:07:16,790 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:14:27,901 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=11389
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.7391985654830933
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Steps = 28800/278576
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:14:32,042 - crisis_transformers.trainer - INFO - dev_loss = 0.553424 || dev_eval_scores = {'perplexity': 1.7391985654830933}
2020-06-12 05:14:32,043 - crisis_transformers.trainer - INFO - train_loss = 0.7753340601921082
2020-06-12 05:14:32,043 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:21:43,000 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=11789
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.7198398113250732
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Steps = 29200/278576
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:21:46,790 - crisis_transformers.trainer - INFO - dev_loss = 0.542231 || dev_eval_scores = {'perplexity': 1.7198398113250732}
2020-06-12 05:21:46,791 - crisis_transformers.trainer - INFO - train_loss = 0.7709231972694397
2020-06-12 05:21:46,791 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:28:58,330 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:29:02,113 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=12189
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.6953392028808594
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Steps = 29600/278576
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - dev_loss = 0.527883 || dev_eval_scores = {'perplexity': 1.6953392028808594}
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO - train_loss = 0.7663020491600037
2020-06-12 05:29:02,114 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:36:13,699 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=12589
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.684487223625183
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Steps = 30000/278576
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - dev_loss = 0.521461 || dev_eval_scores = {'perplexity': 1.684487223625183}
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO - train_loss = 0.7620025277137756
2020-06-12 05:36:17,973 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:43:29,168 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=12989
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.6656123399734497
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:43:33,180 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:43:33,181 - crisis_transformers.trainer - INFO - Steps = 30400/278576
2020-06-12 05:43:33,181 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:43:33,181 - crisis_transformers.trainer - INFO - dev_loss = 0.510193 || dev_eval_scores = {'perplexity': 1.6656123399734497}
2020-06-12 05:43:33,181 - crisis_transformers.trainer - INFO - train_loss = 0.7573661208152771
2020-06-12 05:43:33,181 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:50:44,231 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=13389
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.651535987854004
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Steps = 30800/278576
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:50:48,564 - crisis_transformers.trainer - INFO - dev_loss = 0.501706 || dev_eval_scores = {'perplexity': 1.651535987854004}
2020-06-12 05:50:48,565 - crisis_transformers.trainer - INFO - train_loss = 0.7526668906211853
2020-06-12 05:50:48,565 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 05:57:59,864 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:58:03,697 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=13789
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.6361221075057983
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Steps = 31200/278576
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - dev_loss = 0.492329 || dev_eval_scores = {'perplexity': 1.6361221075057983}
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO - train_loss = 0.7481159567832947
2020-06-12 05:58:03,698 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:05:14,807 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:05:18,556 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=14189
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.6220632791519165
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Steps = 31600/278576
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - dev_loss = 0.483699 || dev_eval_scores = {'perplexity': 1.6220632791519165}
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO - train_loss = 0.7438127994537354
2020-06-12 06:05:18,557 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:12:30,611 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=14589
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:12:34,360 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.610316276550293
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Steps = 32000/278576
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - dev_loss = 0.476431 || dev_eval_scores = {'perplexity': 1.610316276550293}
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO - train_loss = 0.7390771508216858
2020-06-12 06:12:34,361 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:19:45,562 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=14989
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.5992158651351929
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Steps = 32400/278576
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:19:49,380 - crisis_transformers.trainer - INFO - dev_loss = 0.469513 || dev_eval_scores = {'perplexity': 1.5992158651351929}
2020-06-12 06:19:49,381 - crisis_transformers.trainer - INFO - train_loss = 0.7345605492591858
2020-06-12 06:19:49,381 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:27:00,549 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:27:04,344 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=15389
2020-06-12 06:27:04,344 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:27:04,344 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.581007480621338
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Steps = 32800/278576
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - dev_loss = 0.458062 || dev_eval_scores = {'perplexity': 1.581007480621338}
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO - train_loss = 0.7301263809204102
2020-06-12 06:27:04,345 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:34:16,032 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=15789
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.571539044380188
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Steps = 33200/278576
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:34:19,879 - crisis_transformers.trainer - INFO - dev_loss = 0.452055 || dev_eval_scores = {'perplexity': 1.571539044380188}
2020-06-12 06:34:19,880 - crisis_transformers.trainer - INFO - train_loss = 0.7254016399383545
2020-06-12 06:34:19,880 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:41:30,980 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:41:34,818 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=16189
2020-06-12 06:41:34,818 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.5561637878417969
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Steps = 33600/278576
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - dev_loss = 0.442224 || dev_eval_scores = {'perplexity': 1.5561637878417969}
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO - train_loss = 0.7213504314422607
2020-06-12 06:41:34,819 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:48:46,476 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=16589
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.5447299480438232
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:48:50,324 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - Steps = 34000/278576
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - dev_loss = 0.434849 || dev_eval_scores = {'perplexity': 1.5447299480438232}
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO - train_loss = 0.7172350883483887
2020-06-12 06:48:50,325 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 06:56:02,163 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=16989
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.5317991971969604
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Steps = 34400/278576
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - dev_loss = 0.426443 || dev_eval_scores = {'perplexity': 1.5317991971969604}
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO - train_loss = 0.7126625180244446
2020-06-12 06:56:05,999 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:03:17,948 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Save check-point at epoch=1 step=17389
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.5181857347488403
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Epoch = 2/16
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Steps = 34800/278576
2020-06-12 07:03:22,232 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:03:22,233 - crisis_transformers.trainer - INFO - dev_loss = 0.417516 || dev_eval_scores = {'perplexity': 1.5181857347488403}
2020-06-12 07:03:22,233 - crisis_transformers.trainer - INFO - train_loss = 0.7084499001502991
2020-06-12 07:03:22,233 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:03:34,765 - crisis_transformers.trainer - INFO - epoch 2 ends, 14 epoches left
2020-06-12 07:03:34,767 - crisis_transformers.trainer - INFO -
global_average_loss=1.457897663116455,global_steps=34822 on training set
2020-06-12 07:10:33,578 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=378
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.5065593719482422
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Steps = 35200/278576
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:10:37,319 - crisis_transformers.trainer - INFO - dev_loss = 0.409828 || dev_eval_scores = {'perplexity': 1.5065593719482422}
2020-06-12 07:10:37,320 - crisis_transformers.trainer - INFO - train_loss = 0.5077053904533386
2020-06-12 07:10:37,320 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:17:48,578 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:17:52,866 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=778
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4995406866073608
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Steps = 35600/278576
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:17:52,867 - crisis_transformers.trainer - INFO - dev_loss = 0.405159 || dev_eval_scores = {'perplexity': 1.4995406866073608}
2020-06-12 07:17:52,868 - crisis_transformers.trainer - INFO - train_loss = 0.5084229111671448
2020-06-12 07:17:52,868 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:25:04,279 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=1178
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4872630834579468
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Steps = 36000/278576
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - dev_loss = 0.396938 || dev_eval_scores = {'perplexity': 1.4872630834579468}
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO - train_loss = 0.5008477568626404
2020-06-12 07:25:08,441 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:32:19,554 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=1578
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4724860191345215
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Steps = 36400/278576
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - dev_loss = 0.386952 || dev_eval_scores = {'perplexity': 1.4724860191345215}
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO - train_loss = 0.49597886204719543
2020-06-12 07:32:23,792 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:39:35,241 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=1978
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:39:39,063 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4704307317733765
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Steps = 36800/278576
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - dev_loss = 0.385555 || dev_eval_scores = {'perplexity': 1.4704307317733765}
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO - train_loss = 0.4925973117351532
2020-06-12 07:39:39,064 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:46:50,212 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:46:54,091 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=2378
2020-06-12 07:46:54,091 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4530060291290283
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Steps = 37200/278576
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - dev_loss = 0.373635 || dev_eval_scores = {'perplexity': 1.4530060291290283}
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO - train_loss = 0.4874938130378723
2020-06-12 07:46:54,092 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 07:54:05,635 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=2778
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4396711587905884
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Steps = 37600/278576
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 07:54:09,864 - crisis_transformers.trainer - INFO - dev_loss = 0.364415 || dev_eval_scores = {'perplexity': 1.4396711587905884}
2020-06-12 07:54:09,865 - crisis_transformers.trainer - INFO - train_loss = 0.4848006069660187
2020-06-12 07:54:09,865 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:01:21,053 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:01:25,371 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=3178
2020-06-12 08:01:25,371 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:01:25,371 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4313539266586304
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Steps = 38000/278576
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - dev_loss = 0.358621 || dev_eval_scores = {'perplexity': 1.4313539266586304}
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO - train_loss = 0.4819473922252655
2020-06-12 08:01:25,372 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:08:36,819 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=3578
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4217482805252075
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Steps = 38400/278576
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:08:40,629 - crisis_transformers.trainer - INFO - dev_loss = 0.351887 || dev_eval_scores = {'perplexity': 1.4217482805252075}
2020-06-12 08:08:40,630 - crisis_transformers.trainer - INFO - train_loss = 0.47801968455314636
2020-06-12 08:08:40,630 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:15:51,675 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:15:55,394 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=3978
2020-06-12 08:15:55,394 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:15:55,394 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4130357503890991
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Steps = 38800/278576
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - dev_loss = 0.345740 || dev_eval_scores = {'perplexity': 1.4130357503890991}
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO - train_loss = 0.4750809073448181
2020-06-12 08:15:55,395 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:23:07,471 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=4378
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.4030141830444336
2020-06-12 08:23:11,318 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - Steps = 39200/278576
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - dev_loss = 0.338623 || dev_eval_scores = {'perplexity': 1.4030141830444336}
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO - train_loss = 0.4713905453681946
2020-06-12 08:23:11,319 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:30:22,512 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=4778
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.391721487045288
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:30:26,227 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO - Steps = 39600/278576
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO - dev_loss = 0.330542 || dev_eval_scores = {'perplexity': 1.391721487045288}
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO - train_loss = 0.4688350260257721
2020-06-12 08:30:26,228 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:37:37,836 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=5178
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3863202333450317
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Steps = 40000/278576
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:37:41,641 - crisis_transformers.trainer - INFO - dev_loss = 0.326653 || dev_eval_scores = {'perplexity': 1.3863202333450317}
2020-06-12 08:37:41,642 - crisis_transformers.trainer - INFO - train_loss = 0.4653063714504242
2020-06-12 08:37:41,642 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:44:52,891 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:44:56,707 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=5578
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3764472007751465
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Steps = 40400/278576
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - dev_loss = 0.319506 || dev_eval_scores = {'perplexity': 1.3764472007751465}
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO - train_loss = 0.4616211950778961
2020-06-12 08:44:56,708 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:52:07,568 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=5978
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3701869249343872
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Steps = 40800/278576
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - dev_loss = 0.314947 || dev_eval_scores = {'perplexity': 1.3701869249343872}
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO - train_loss = 0.4588777422904968
2020-06-12 08:52:11,277 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 08:59:22,571 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=6378
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3665746450424194
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Steps = 41200/278576
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - dev_loss = 0.312307 || dev_eval_scores = {'perplexity': 1.3665746450424194}
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO - train_loss = 0.4553696811199188
2020-06-12 08:59:26,446 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:06:37,730 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=6778
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.35618257522583
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:06:41,569 - crisis_transformers.trainer - INFO - Steps = 41600/278576
2020-06-12 09:06:41,570 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:06:41,570 - crisis_transformers.trainer - INFO - dev_loss = 0.304674 || dev_eval_scores = {'perplexity': 1.35618257522583}
2020-06-12 09:06:41,570 - crisis_transformers.trainer - INFO - train_loss = 0.4522298574447632
2020-06-12 09:06:41,570 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:13:52,744 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:13:56,458 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=7178
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.347740888595581
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Steps = 42000/278576
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - dev_loss = 0.298430 || dev_eval_scores = {'perplexity': 1.347740888595581}
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO - train_loss = 0.4496159553527832
2020-06-12 09:13:56,459 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:21:07,688 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=7578
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3386039733886719
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Steps = 42400/278576
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:21:11,509 - crisis_transformers.trainer - INFO - dev_loss = 0.291627 || dev_eval_scores = {'perplexity': 1.3386039733886719}
2020-06-12 09:21:11,510 - crisis_transformers.trainer - INFO - train_loss = 0.44657158851623535
2020-06-12 09:21:11,510 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:28:22,370 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=7978
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3325072526931763
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Steps = 42800/278576
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - dev_loss = 0.287062 || dev_eval_scores = {'perplexity': 1.3325072526931763}
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO - train_loss = 0.4432190954685211
2020-06-12 09:28:26,197 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:35:37,349 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=8378
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3274871110916138
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Steps = 43200/278576
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:35:41,210 - crisis_transformers.trainer - INFO - dev_loss = 0.283288 || dev_eval_scores = {'perplexity': 1.3274871110916138}
2020-06-12 09:35:41,211 - crisis_transformers.trainer - INFO - train_loss = 0.4402396082878113
2020-06-12 09:35:41,211 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:42:52,444 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=8778
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.315727710723877
2020-06-12 09:42:56,294 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - Steps = 43600/278576
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - dev_loss = 0.274390 || dev_eval_scores = {'perplexity': 1.315727710723877}
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO - train_loss = 0.43725401163101196
2020-06-12 09:42:56,295 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:50:07,902 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=9178
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3152892589569092
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Steps = 44000/278576
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - dev_loss = 0.274057 || dev_eval_scores = {'perplexity': 1.3152892589569092}
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO - train_loss = 0.43421682715415955
2020-06-12 09:50:12,219 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 09:57:23,789 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:57:27,692 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=9578
2020-06-12 09:57:27,692 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 09:57:27,692 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.306022047996521
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Steps = 44400/278576
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - dev_loss = 0.266986 || dev_eval_scores = {'perplexity': 1.306022047996521}
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO - train_loss = 0.43124547600746155
2020-06-12 09:57:27,693 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:04:38,908 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:04:42,860 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=9978
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.3020490407943726
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Steps = 44800/278576
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - dev_loss = 0.263939 || dev_eval_scores = {'perplexity': 1.3020490407943726}
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO - train_loss = 0.42827215790748596
2020-06-12 10:04:42,861 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:11:53,676 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:11:57,556 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=10378
2020-06-12 10:11:57,556 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:11:57,556 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:11:57,556 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:11:57,556 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2914035320281982
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Steps = 45200/278576
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - dev_loss = 0.255730 || dev_eval_scores = {'perplexity': 1.2914035320281982}
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO - train_loss = 0.4252185821533203
2020-06-12 10:11:57,557 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:19:08,790 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=10778
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2862516641616821
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 10:19:12,161 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:19:12,162 - crisis_transformers.trainer - INFO - Steps = 45600/278576
2020-06-12 10:19:12,162 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:19:12,162 - crisis_transformers.trainer - INFO - dev_loss = 0.251732 || dev_eval_scores = {'perplexity': 1.2862516641616821}
2020-06-12 10:19:12,162 - crisis_transformers.trainer - INFO - train_loss = 0.4227924942970276
2020-06-12 10:19:12,162 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:26:22,943 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:26:27,198 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=11178
2020-06-12 10:26:27,198 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:26:27,198 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.282753825187683
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Steps = 46000/278576
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - dev_loss = 0.249009 || dev_eval_scores = {'perplexity': 1.282753825187683}
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO - train_loss = 0.41981765627861023
2020-06-12 10:26:27,199 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:33:37,608 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:33:41,331 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=11578
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2747212648391724
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Steps = 46400/278576
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - dev_loss = 0.242728 || dev_eval_scores = {'perplexity': 1.2747212648391724}
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO - train_loss = 0.41709834337234497
2020-06-12 10:33:41,332 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:40:52,557 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=11978
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.270970106124878
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Steps = 46800/278576
2020-06-12 10:40:56,240 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:40:56,241 - crisis_transformers.trainer - INFO - dev_loss = 0.239781 || dev_eval_scores = {'perplexity': 1.270970106124878}
2020-06-12 10:40:56,241 - crisis_transformers.trainer - INFO - train_loss = 0.41438814997673035
2020-06-12 10:40:56,241 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:48:07,184 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=12378
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2681171894073486
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Steps = 47200/278576
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:48:11,365 - crisis_transformers.trainer - INFO - dev_loss = 0.237533 || dev_eval_scores = {'perplexity': 1.2681171894073486}
2020-06-12 10:48:11,366 - crisis_transformers.trainer - INFO - train_loss = 0.4116062819957733
2020-06-12 10:48:11,366 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 10:55:21,839 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 10:55:21,839 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2681171894073486
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 10s
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Steps = 47600/278576
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - dev_loss = 0.237603 || dev_eval_scores = {'perplexity': 1.268206000328064}
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO - train_loss = 0.4090476334095001
2020-06-12 10:55:21,840 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:02:33,440 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=13178
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2570724487304688
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Steps = 48000/278576
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - dev_loss = 0.228786 || dev_eval_scores = {'perplexity': 1.2570724487304688}
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO - train_loss = 0.40632161498069763
2020-06-12 11:02:37,076 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:09:48,383 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:09:51,983 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=13578
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.252106785774231
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Steps = 48400/278576
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - dev_loss = 0.224828 || dev_eval_scores = {'perplexity': 1.252106785774231}
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO - train_loss = 0.40354153513908386
2020-06-12 11:09:51,984 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:17:03,692 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=13978
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2468602657318115
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:17:07,245 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 11:17:07,246 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:17:07,246 - crisis_transformers.trainer - INFO - Steps = 48800/278576
2020-06-12 11:17:07,246 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:17:07,246 - crisis_transformers.trainer - INFO - dev_loss = 0.220629 || dev_eval_scores = {'perplexity': 1.2468602657318115}
2020-06-12 11:17:07,246 - crisis_transformers.trainer - INFO - train_loss = 0.40087953209877014
2020-06-12 11:17:07,246 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:24:17,752 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:24:21,750 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=14378
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.241665244102478
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Steps = 49200/278576
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - dev_loss = 0.216453 || dev_eval_scores = {'perplexity': 1.241665244102478}
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO - train_loss = 0.3984794318675995
2020-06-12 11:24:21,751 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:31:32,613 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:31:36,096 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=14778
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2373579740524292
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Steps = 49600/278576
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - dev_loss = 0.212978 || dev_eval_scores = {'perplexity': 1.2373579740524292}
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO - train_loss = 0.3960722088813782
2020-06-12 11:31:36,097 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:38:48,257 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=15178
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2339407205581665
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Steps = 50000/278576
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - dev_loss = 0.210213 || dev_eval_scores = {'perplexity': 1.2339407205581665}
2020-06-12 11:38:51,723 - crisis_transformers.trainer - INFO - train_loss = 0.39352700114250183
2020-06-12 11:38:51,724 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:46:03,817 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=15578
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2312901020050049
2020-06-12 11:46:07,113 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - Steps = 50400/278576
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - dev_loss = 0.208062 || dev_eval_scores = {'perplexity': 1.2312901020050049}
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO - train_loss = 0.39096903800964355
2020-06-12 11:46:07,114 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 11:53:18,503 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:53:21,880 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=15978
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2268590927124023
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Steps = 50800/278576
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 11:53:21,881 - crisis_transformers.trainer - INFO - dev_loss = 0.204457 || dev_eval_scores = {'perplexity': 1.2268590927124023}
2020-06-12 11:53:21,882 - crisis_transformers.trainer - INFO - train_loss = 0.3884601294994354
2020-06-12 11:53:21,882 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:00:33,247 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:00:36,497 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=16378
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.224045991897583
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Steps = 51200/278576
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - dev_loss = 0.202162 || dev_eval_scores = {'perplexity': 1.224045991897583}
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO - train_loss = 0.38594967126846313
2020-06-12 12:00:36,498 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:07:47,479 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:07:51,260 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=16778
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.21811842918396
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Steps = 51600/278576
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - dev_loss = 0.197307 || dev_eval_scores = {'perplexity': 1.21811842918396}
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO - train_loss = 0.3834236264228821
2020-06-12 12:07:51,261 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:15:01,910 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:15:05,101 - crisis_transformers.trainer - INFO - Save check-point at epoch=2 step=17178
2020-06-12 12:15:05,103 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:15:05,103 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:15:05,103 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:15:05,103 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:15:05,103 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2158831357955933
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 13s
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Epoch = 3/16
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Steps = 52000/278576
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - dev_loss = 0.195471 || dev_eval_scores = {'perplexity': 1.2158831357955933}
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO - train_loss = 0.3809737265110016
2020-06-12 12:15:05,104 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:17:19,046 - crisis_transformers.trainer - INFO - epoch 3 ends, 13 epoches left
2020-06-12 12:17:19,049 - crisis_transformers.trainer - INFO -
global_average_loss=1.0984210968017578,global_steps=52233 on training set
2020-06-12 12:22:16,490 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=167
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2130458354949951
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Steps = 52400/278576
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:22:19,854 - crisis_transformers.trainer - INFO - dev_loss = 0.193134 || dev_eval_scores = {'perplexity': 1.2130458354949951}
2020-06-12 12:22:19,855 - crisis_transformers.trainer - INFO - train_loss = 0.25673729181289673
2020-06-12 12:22:19,855 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:29:30,907 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=567
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.210909128189087
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:29:34,508 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 12:29:34,509 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 12:29:34,509 - crisis_transformers.trainer - INFO - Steps = 52800/278576
2020-06-12 12:29:34,509 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:29:34,509 - crisis_transformers.trainer - INFO - dev_loss = 0.191371 || dev_eval_scores = {'perplexity': 1.210909128189087}
2020-06-12 12:29:34,509 - crisis_transformers.trainer - INFO - train_loss = 0.25955724716186523
2020-06-12 12:29:34,509 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:36:45,199 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=967
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2072252035140991
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:36:48,918 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:36:48,919 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 12:36:48,919 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 12:36:48,919 - crisis_transformers.trainer - INFO - Steps = 53200/278576
2020-06-12 12:36:48,919 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:36:48,919 - crisis_transformers.trainer - INFO - dev_loss = 0.188325 || dev_eval_scores = {'perplexity': 1.2072252035140991}
2020-06-12 12:36:48,919 - crisis_transformers.trainer - INFO - train_loss = 0.2595442533493042
2020-06-12 12:36:48,920 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:43:59,962 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:44:03,265 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=1367
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2031614780426025
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:44:03,280 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:44:03,281 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 12:44:03,281 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 12:44:03,281 - crisis_transformers.trainer - INFO - Steps = 53600/278576
2020-06-12 12:44:03,281 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:44:03,282 - crisis_transformers.trainer - INFO - dev_loss = 0.184953 || dev_eval_scores = {'perplexity': 1.2031614780426025}
2020-06-12 12:44:03,297 - crisis_transformers.trainer - INFO - train_loss = 0.25946447253227234
2020-06-12 12:44:03,297 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:51:15,360 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:51:18,633 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=1767
2020-06-12 12:51:18,648 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:51:18,648 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2021421194076538
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:51:18,649 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:51:18,650 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 12:51:18,650 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 12:51:18,650 - crisis_transformers.trainer - INFO - Steps = 54000/278576
2020-06-12 12:51:18,650 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:51:18,650 - crisis_transformers.trainer - INFO - dev_loss = 0.184105 || dev_eval_scores = {'perplexity': 1.2021421194076538}
2020-06-12 12:51:18,669 - crisis_transformers.trainer - INFO - train_loss = 0.2583455443382263
2020-06-12 12:51:18,669 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2021421194076538
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Steps = 54400/278576
2020-06-12 12:58:30,080 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 12:58:30,081 - crisis_transformers.trainer - INFO - dev_loss = 0.184208 || dev_eval_scores = {'perplexity': 1.2022662162780762}
2020-06-12 12:58:30,081 - crisis_transformers.trainer - INFO - train_loss = 0.25629064440727234
2020-06-12 12:58:30,081 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:05:42,132 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2021421194076538
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:05:42,133 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO - Steps = 54800/278576
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO - dev_loss = 0.187595 || dev_eval_scores = {'perplexity': 1.2063448429107666}
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO - train_loss = 0.25469452142715454
2020-06-12 13:05:42,134 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:12:53,734 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:12:53,736 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:12:53,736 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:12:53,736 - crisis_transformers.trainer - INFO - Early stop count = 3/20
2020-06-12 13:12:53,736 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:12:53,736 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.2021421194076538
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Steps = 55200/278576
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - dev_loss = 0.184251 || dev_eval_scores = {'perplexity': 1.2023180723190308}
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO - train_loss = 0.25338509678840637
2020-06-12 13:12:53,737 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:20:04,638 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:20:07,839 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=3367
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.191463589668274
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:20:07,854 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:20:07,855 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 13:20:07,856 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:20:07,856 - crisis_transformers.trainer - INFO - Steps = 55600/278576
2020-06-12 13:20:07,856 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:20:07,856 - crisis_transformers.trainer - INFO - dev_loss = 0.175182 || dev_eval_scores = {'perplexity': 1.191463589668274}
2020-06-12 13:20:07,876 - crisis_transformers.trainer - INFO - train_loss = 0.2521595358848572
2020-06-12 13:20:07,876 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:27:19,652 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:27:22,821 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=3767
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1891900300979614
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:27:22,836 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:27:22,837 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:27:22,837 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 13:27:22,837 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:27:22,837 - crisis_transformers.trainer - INFO - Steps = 56000/278576
2020-06-12 13:27:22,837 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:27:22,837 - crisis_transformers.trainer - INFO - dev_loss = 0.173272 || dev_eval_scores = {'perplexity': 1.1891900300979614}
2020-06-12 13:27:22,856 - crisis_transformers.trainer - INFO - train_loss = 0.251168429851532
2020-06-12 13:27:22,856 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1891900300979614
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Steps = 56400/278576
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - dev_loss = 0.174895 || dev_eval_scores = {'perplexity': 1.1911215782165527}
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO - train_loss = 0.2495262175798416
2020-06-12 13:34:34,678 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:41:45,895 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:41:49,254 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=4567
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1830016374588013
2020-06-12 13:41:49,270 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:41:49,271 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:41:49,271 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:41:49,272 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 13:41:49,272 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:41:49,272 - crisis_transformers.trainer - INFO - Steps = 56800/278576
2020-06-12 13:41:49,272 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:41:49,272 - crisis_transformers.trainer - INFO - dev_loss = 0.168055 || dev_eval_scores = {'perplexity': 1.1830016374588013}
2020-06-12 13:41:49,290 - crisis_transformers.trainer - INFO - train_loss = 0.24820448458194733
2020-06-12 13:41:49,290 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:49:01,184 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:49:04,330 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=4967
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1823091506958008
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:49:04,346 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:49:04,348 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 13:49:04,348 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:49:04,348 - crisis_transformers.trainer - INFO - Steps = 57200/278576
2020-06-12 13:49:04,348 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:49:04,348 - crisis_transformers.trainer - INFO - dev_loss = 0.167469 || dev_eval_scores = {'perplexity': 1.1823091506958008}
2020-06-12 13:49:04,366 - crisis_transformers.trainer - INFO - train_loss = 0.24676309525966644
2020-06-12 13:49:04,366 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1823091506958008
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Steps = 57600/278576
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - dev_loss = 0.168122 || dev_eval_scores = {'perplexity': 1.1830805540084839}
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO - train_loss = 0.2456163614988327
2020-06-12 13:56:16,108 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:03:27,611 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1823091506958008
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 14:03:27,612 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:03:27,613 - crisis_transformers.trainer - INFO - Steps = 58000/278576
2020-06-12 14:03:27,613 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:03:27,613 - crisis_transformers.trainer - INFO - dev_loss = 0.168360 || dev_eval_scores = {'perplexity': 1.1833629608154297}
2020-06-12 14:03:27,613 - crisis_transformers.trainer - INFO - train_loss = 0.24447211623191833
2020-06-12 14:03:27,613 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:10:39,369 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:10:42,563 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=6167
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1757748126983643
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:10:42,580 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:10:42,581 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 14:10:42,581 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:10:42,581 - crisis_transformers.trainer - INFO - Steps = 58400/278576
2020-06-12 14:10:42,581 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:10:42,581 - crisis_transformers.trainer - INFO - dev_loss = 0.161927 || dev_eval_scores = {'perplexity': 1.1757748126983643}
2020-06-12 14:10:42,599 - crisis_transformers.trainer - INFO - train_loss = 0.24326415359973907
2020-06-12 14:10:42,599 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:17:54,473 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:17:57,675 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=6567
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1724531650543213
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:17:57,691 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:17:57,692 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 14:17:57,692 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:17:57,692 - crisis_transformers.trainer - INFO - Steps = 58800/278576
2020-06-12 14:17:57,692 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:17:57,692 - crisis_transformers.trainer - INFO - dev_loss = 0.159098 || dev_eval_scores = {'perplexity': 1.1724531650543213}
2020-06-12 14:17:57,710 - crisis_transformers.trainer - INFO - train_loss = 0.24194355309009552
2020-06-12 14:17:57,710 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:25:09,648 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:25:13,392 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=6967
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1723699569702148
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:25:13,407 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:25:13,408 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 14:25:13,408 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:25:13,408 - crisis_transformers.trainer - INFO - Steps = 59200/278576
2020-06-12 14:25:13,408 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:25:13,408 - crisis_transformers.trainer - INFO - dev_loss = 0.159027 || dev_eval_scores = {'perplexity': 1.1723699569702148}
2020-06-12 14:25:13,426 - crisis_transformers.trainer - INFO - train_loss = 0.24068011343479156
2020-06-12 14:25:13,426 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:32:25,725 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:32:28,988 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=7367
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1677402257919312
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:32:29,004 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:32:29,005 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 14:32:29,005 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:32:29,005 - crisis_transformers.trainer - INFO - Steps = 59600/278576
2020-06-12 14:32:29,005 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:32:29,005 - crisis_transformers.trainer - INFO - dev_loss = 0.155071 || dev_eval_scores = {'perplexity': 1.1677402257919312}
2020-06-12 14:32:29,024 - crisis_transformers.trainer - INFO - train_loss = 0.23944209516048431
2020-06-12 14:32:29,024 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1677402257919312
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Steps = 60000/278576
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - dev_loss = 0.160010 || dev_eval_scores = {'perplexity': 1.1735223531723022}
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO - train_loss = 0.23837868869304657
2020-06-12 14:39:41,605 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:46:52,988 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:46:55,997 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=8167
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1659613847732544
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:46:56,013 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:46:56,014 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 14:46:56,015 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:46:56,015 - crisis_transformers.trainer - INFO - Steps = 60400/278576
2020-06-12 14:46:56,015 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:46:56,015 - crisis_transformers.trainer - INFO - dev_loss = 0.153546 || dev_eval_scores = {'perplexity': 1.1659613847732544}
2020-06-12 14:46:56,033 - crisis_transformers.trainer - INFO - train_loss = 0.23715026676654816
2020-06-12 14:46:56,033 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 14:54:07,918 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:54:10,976 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=8567
2020-06-12 14:54:10,989 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.165794014930725
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Steps = 60800/278576
2020-06-12 14:54:10,990 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 14:54:10,991 - crisis_transformers.trainer - INFO - dev_loss = 0.153402 || dev_eval_scores = {'perplexity': 1.165794014930725}
2020-06-12 14:54:11,007 - crisis_transformers.trainer - INFO - train_loss = 0.23593905568122864
2020-06-12 14:54:11,007 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:01:22,795 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:01:25,973 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=8967
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.161121129989624
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:01:25,989 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:01:25,990 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 15:01:25,990 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:01:25,990 - crisis_transformers.trainer - INFO - Steps = 61200/278576
2020-06-12 15:01:25,990 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:01:25,990 - crisis_transformers.trainer - INFO - dev_loss = 0.149386 || dev_eval_scores = {'perplexity': 1.161121129989624}
2020-06-12 15:01:26,009 - crisis_transformers.trainer - INFO - train_loss = 0.2347162663936615
2020-06-12 15:01:26,009 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:08:37,941 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:08:41,095 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=9367
2020-06-12 15:08:41,110 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:08:41,110 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:08:41,110 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:08:41,110 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:08:41,111 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:08:41,111 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.159262776374817
2020-06-12 15:08:41,111 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:08:41,111 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:08:41,111 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:08:41,112 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 15:08:41,112 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:08:41,112 - crisis_transformers.trainer - INFO - Steps = 61600/278576
2020-06-12 15:08:41,112 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:08:41,112 - crisis_transformers.trainer - INFO - dev_loss = 0.147784 || dev_eval_scores = {'perplexity': 1.159262776374817}
2020-06-12 15:08:41,131 - crisis_transformers.trainer - INFO - train_loss = 0.2334117591381073
2020-06-12 15:08:41,131 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:15:53,144 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.159262776374817
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Steps = 62000/278576
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - dev_loss = 0.149117 || dev_eval_scores = {'perplexity': 1.1608085632324219}
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO - train_loss = 0.23231545090675354
2020-06-12 15:15:53,145 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:23:04,214 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:23:07,484 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=10167
2020-06-12 15:23:07,500 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:23:07,500 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:23:07,500 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:23:07,500 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:23:07,500 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:23:07,500 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1586897373199463
2020-06-12 15:23:07,501 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:23:07,501 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:23:07,501 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:23:07,502 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 15:23:07,502 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:23:07,502 - crisis_transformers.trainer - INFO - Steps = 62400/278576
2020-06-12 15:23:07,502 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:23:07,502 - crisis_transformers.trainer - INFO - dev_loss = 0.147290 || dev_eval_scores = {'perplexity': 1.1586897373199463}
2020-06-12 15:23:07,520 - crisis_transformers.trainer - INFO - train_loss = 0.23095978796482086
2020-06-12 15:23:07,520 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:30:19,155 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:30:22,774 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=10567
2020-06-12 15:30:22,775 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:30:22,775 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:30:22,775 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:30:22,775 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:30:22,775 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:30:22,776 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.155853509902954
2020-06-12 15:30:22,776 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:30:22,776 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:30:22,776 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO - Steps = 62800/278576
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO - dev_loss = 0.144839 || dev_eval_scores = {'perplexity': 1.155853509902954}
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO - train_loss = 0.22986294329166412
2020-06-12 15:30:22,777 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:37:34,325 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:37:34,325 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.155853509902954
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Steps = 63200/278576
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - dev_loss = 0.146531 || dev_eval_scores = {'perplexity': 1.1578106880187988}
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO - train_loss = 0.2286159247159958
2020-06-12 15:37:34,326 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:44:45,801 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:44:48,841 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=11367
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1531232595443726
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:44:48,857 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:44:48,858 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 15:44:48,858 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:44:48,858 - crisis_transformers.trainer - INFO - Steps = 63600/278576
2020-06-12 15:44:48,858 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:44:48,858 - crisis_transformers.trainer - INFO - dev_loss = 0.142474 || dev_eval_scores = {'perplexity': 1.1531232595443726}
2020-06-12 15:44:48,865 - crisis_transformers.trainer - INFO - train_loss = 0.22760188579559326
2020-06-12 15:44:48,865 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:52:00,452 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:52:04,180 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=11767
2020-06-12 15:52:04,195 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1524842977523804
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:52:04,196 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:52:04,197 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 15:52:04,197 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:52:04,197 - crisis_transformers.trainer - INFO - Steps = 64000/278576
2020-06-12 15:52:04,197 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:52:04,197 - crisis_transformers.trainer - INFO - dev_loss = 0.141920 || dev_eval_scores = {'perplexity': 1.1524842977523804}
2020-06-12 15:52:04,203 - crisis_transformers.trainer - INFO - train_loss = 0.22645704448223114
2020-06-12 15:52:04,203 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 15:59:15,356 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:59:18,493 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=12167
2020-06-12 15:59:18,496 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 15:59:18,496 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 15:59:18,496 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 15:59:18,496 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 15:59:18,496 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 15:59:18,497 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1517306566238403
2020-06-12 15:59:18,497 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 15:59:18,497 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 15:59:18,497 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 15:59:18,498 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 15:59:18,498 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 15:59:18,498 - crisis_transformers.trainer - INFO - Steps = 64400/278576
2020-06-12 15:59:18,498 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 15:59:18,498 - crisis_transformers.trainer - INFO - dev_loss = 0.141266 || dev_eval_scores = {'perplexity': 1.1517306566238403}
2020-06-12 15:59:18,511 - crisis_transformers.trainer - INFO - train_loss = 0.22518599033355713
2020-06-12 15:59:18,511 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:06:30,098 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:06:33,674 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=12567
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1506377458572388
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:06:33,689 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:06:33,690 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 16:06:33,690 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:06:33,690 - crisis_transformers.trainer - INFO - Steps = 64800/278576
2020-06-12 16:06:33,690 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:06:33,690 - crisis_transformers.trainer - INFO - dev_loss = 0.140316 || dev_eval_scores = {'perplexity': 1.1506377458572388}
2020-06-12 16:06:33,705 - crisis_transformers.trainer - INFO - train_loss = 0.2241048812866211
2020-06-12 16:06:33,705 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:13:44,939 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:13:48,305 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=12967
2020-06-12 16:13:48,319 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:13:48,319 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1486502885818481
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:13:48,320 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:13:48,321 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 16:13:48,321 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:13:48,321 - crisis_transformers.trainer - INFO - Steps = 65200/278576
2020-06-12 16:13:48,321 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:13:48,321 - crisis_transformers.trainer - INFO - dev_loss = 0.138588 || dev_eval_scores = {'perplexity': 1.1486502885818481}
2020-06-12 16:13:48,348 - crisis_transformers.trainer - INFO - train_loss = 0.22296540439128876
2020-06-12 16:13:48,348 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:21:01,926 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:21:05,595 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=13367
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1468722820281982
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:21:05,596 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 17s
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO - Steps = 65600/278576
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO - dev_loss = 0.137039 || dev_eval_scores = {'perplexity': 1.1468722820281982}
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO - train_loss = 0.2220388650894165
2020-06-12 16:21:05,597 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:28:16,835 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:28:20,007 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=13767
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1454410552978516
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:28:20,008 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:28:20,009 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 16:28:20,009 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:28:20,009 - crisis_transformers.trainer - INFO - Steps = 66000/278576
2020-06-12 16:28:20,009 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:28:20,009 - crisis_transformers.trainer - INFO - dev_loss = 0.135790 || dev_eval_scores = {'perplexity': 1.1454410552978516}
2020-06-12 16:28:20,010 - crisis_transformers.trainer - INFO - train_loss = 0.22106683254241943
2020-06-12 16:28:20,010 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:35:31,636 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:35:35,306 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=14167
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1435331106185913
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:35:35,322 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:35:35,323 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 16:35:35,323 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:35:35,323 - crisis_transformers.trainer - INFO - Steps = 66400/278576
2020-06-12 16:35:35,323 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:35:35,323 - crisis_transformers.trainer - INFO - dev_loss = 0.134123 || dev_eval_scores = {'perplexity': 1.1435331106185913}
2020-06-12 16:35:35,324 - crisis_transformers.trainer - INFO - train_loss = 0.2200937420129776
2020-06-12 16:35:35,324 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:42:46,589 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:42:46,589 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:42:46,589 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:42:46,589 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1435331106185913
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Steps = 66800/278576
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - dev_loss = 0.139419 || dev_eval_scores = {'perplexity': 1.1496059894561768}
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO - train_loss = 0.21907271444797516
2020-06-12 16:42:46,590 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:49:57,796 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:50:01,478 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=14967
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1425509452819824
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:50:01,491 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:50:01,492 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 16:50:01,492 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:50:01,492 - crisis_transformers.trainer - INFO - Steps = 67200/278576
2020-06-12 16:50:01,492 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:50:01,492 - crisis_transformers.trainer - INFO - dev_loss = 0.133263 || dev_eval_scores = {'perplexity': 1.1425509452819824}
2020-06-12 16:50:01,500 - crisis_transformers.trainer - INFO - train_loss = 0.2180401235818863
2020-06-12 16:50:01,500 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 16:57:12,820 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:57:15,939 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=15367
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1421887874603271
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 16:57:15,940 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO - Steps = 67600/278576
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO - dev_loss = 0.132946 || dev_eval_scores = {'perplexity': 1.1421887874603271}
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO - train_loss = 0.2170739322900772
2020-06-12 16:57:15,941 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:04:27,191 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:04:27,191 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:04:27,191 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:04:27,191 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 17:04:27,191 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:04:27,191 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1421887874603271
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Steps = 68000/278576
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - dev_loss = 0.133038 || dev_eval_scores = {'perplexity': 1.1422935724258423}
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO - train_loss = 0.21610437333583832
2020-06-12 17:04:27,192 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:11:38,816 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:11:41,945 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=16167
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1390084028244019
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:11:41,958 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:11:41,959 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 17:11:41,959 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 17:11:41,959 - crisis_transformers.trainer - INFO - Steps = 68400/278576
2020-06-12 17:11:41,959 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:11:41,959 - crisis_transformers.trainer - INFO - dev_loss = 0.130158 || dev_eval_scores = {'perplexity': 1.1390084028244019}
2020-06-12 17:11:41,975 - crisis_transformers.trainer - INFO - train_loss = 0.21520239114761353
2020-06-12 17:11:41,975 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:18:54,648 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:18:54,648 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1390084028244019
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:18:54,649 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO - Steps = 68800/278576
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO - dev_loss = 0.130209 || dev_eval_scores = {'perplexity': 1.1390659809112549}
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO - train_loss = 0.21429920196533203
2020-06-12 17:18:54,650 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:26:06,245 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1390084028244019
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Steps = 69200/278576
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - dev_loss = 0.131858 || dev_eval_scores = {'perplexity': 1.1409462690353394}
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO - train_loss = 0.2133215069770813
2020-06-12 17:26:06,248 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:33:18,361 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:33:21,478 - crisis_transformers.trainer - INFO - Save check-point at epoch=3 step=17367
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.135805368423462
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:33:21,481 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:33:21,483 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 17:33:21,483 - crisis_transformers.trainer - INFO - Epoch = 4/16
2020-06-12 17:33:21,483 - crisis_transformers.trainer - INFO - Steps = 69600/278576
2020-06-12 17:33:21,483 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:33:21,483 - crisis_transformers.trainer - INFO - dev_loss = 0.127342 || dev_eval_scores = {'perplexity': 1.135805368423462}
2020-06-12 17:33:21,485 - crisis_transformers.trainer - INFO - train_loss = 0.21238122880458832
2020-06-12 17:33:21,485 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:33:46,659 - crisis_transformers.trainer - INFO - epoch 4 ends, 12 epoches left
2020-06-12 17:33:46,661 - crisis_transformers.trainer - INFO -
global_average_loss=0.8768848776817322,global_steps=69644 on training set
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.135805368423462
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Steps = 70000/278576
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:40:33,522 - crisis_transformers.trainer - INFO - dev_loss = 0.129323 || dev_eval_scores = {'perplexity': 1.138058066368103}
2020-06-12 17:40:33,523 - crisis_transformers.trainer - INFO - train_loss = 0.16184912621974945
2020-06-12 17:40:33,523 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.135805368423462
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Steps = 70400/278576
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - dev_loss = 0.127871 || dev_eval_scores = {'perplexity': 1.1364060640335083}
2020-06-12 17:47:45,699 - crisis_transformers.trainer - INFO - train_loss = 0.16288244724273682
2020-06-12 17:47:45,700 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 17:54:57,738 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:55:00,860 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=1156
2020-06-12 17:55:00,875 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 17:55:00,875 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 17:55:00,875 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 17:55:00,875 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 17:55:00,875 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 17:55:00,876 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1350326538085938
2020-06-12 17:55:00,876 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 17:55:00,876 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 17:55:00,876 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 17:55:00,876 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 17:55:00,877 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 17:55:00,877 - crisis_transformers.trainer - INFO - Steps = 70800/278576
2020-06-12 17:55:00,877 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 17:55:00,877 - crisis_transformers.trainer - INFO - dev_loss = 0.126661 || dev_eval_scores = {'perplexity': 1.1350326538085938}
2020-06-12 17:55:00,894 - crisis_transformers.trainer - INFO - train_loss = 0.16178201138973236
2020-06-12 17:55:00,894 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:02:13,264 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:02:16,346 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=1556
2020-06-12 18:02:16,360 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:02:16,360 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:02:16,360 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:02:16,360 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1342060565948486
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 18:02:16,361 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:02:16,362 - crisis_transformers.trainer - INFO - Steps = 71200/278576
2020-06-12 18:02:16,362 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:02:16,362 - crisis_transformers.trainer - INFO - dev_loss = 0.125933 || dev_eval_scores = {'perplexity': 1.1342060565948486}
2020-06-12 18:02:16,378 - crisis_transformers.trainer - INFO - train_loss = 0.16210666298866272
2020-06-12 18:02:16,378 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:09:28,443 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:09:31,521 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=1956
2020-06-12 18:09:31,536 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:09:31,536 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.133441686630249
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:09:31,537 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:09:31,538 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 18:09:31,538 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:09:31,538 - crisis_transformers.trainer - INFO - Steps = 71600/278576
2020-06-12 18:09:31,538 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:09:31,539 - crisis_transformers.trainer - INFO - dev_loss = 0.125259 || dev_eval_scores = {'perplexity': 1.133441686630249}
2020-06-12 18:09:31,556 - crisis_transformers.trainer - INFO - train_loss = 0.16150160133838654
2020-06-12 18:09:31,556 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:16:44,613 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:16:47,595 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=2356
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1324461698532104
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:16:47,596 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:16:47,597 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 18:16:47,597 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:16:47,597 - crisis_transformers.trainer - INFO - Steps = 72000/278576
2020-06-12 18:16:47,597 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:16:47,597 - crisis_transformers.trainer - INFO - dev_loss = 0.124380 || dev_eval_scores = {'perplexity': 1.1324461698532104}
2020-06-12 18:16:47,597 - crisis_transformers.trainer - INFO - train_loss = 0.160808727145195
2020-06-12 18:16:47,598 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:23:59,557 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:24:02,688 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=2756
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1319714784622192
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:24:02,703 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:24:02,704 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 18:24:02,704 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:24:02,704 - crisis_transformers.trainer - INFO - Steps = 72400/278576
2020-06-12 18:24:02,704 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:24:02,704 - crisis_transformers.trainer - INFO - dev_loss = 0.123961 || dev_eval_scores = {'perplexity': 1.1319714784622192}
2020-06-12 18:24:02,723 - crisis_transformers.trainer - INFO - train_loss = 0.16037367284297943
2020-06-12 18:24:02,723 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:31:14,824 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:31:17,933 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=3156
2020-06-12 18:31:17,949 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:31:17,949 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:31:17,949 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:31:17,949 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 18:31:17,949 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.131042718887329
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Steps = 72800/278576
2020-06-12 18:31:17,950 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:31:17,951 - crisis_transformers.trainer - INFO - dev_loss = 0.123140 || dev_eval_scores = {'perplexity': 1.131042718887329}
2020-06-12 18:31:17,969 - crisis_transformers.trainer - INFO - train_loss = 0.16030311584472656
2020-06-12 18:31:17,970 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:38:30,048 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:38:33,201 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=3556
2020-06-12 18:38:33,201 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.130492091178894
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 18:38:33,202 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:38:33,203 - crisis_transformers.trainer - INFO - Steps = 73200/278576
2020-06-12 18:38:33,203 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:38:33,203 - crisis_transformers.trainer - INFO - dev_loss = 0.122653 || dev_eval_scores = {'perplexity': 1.130492091178894}
2020-06-12 18:38:33,203 - crisis_transformers.trainer - INFO - train_loss = 0.16008983552455902
2020-06-12 18:38:33,203 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.130492091178894
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:45:45,223 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - Steps = 73600/278576
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - dev_loss = 0.126517 || dev_eval_scores = {'perplexity': 1.1348693370819092}
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO - train_loss = 0.15986071527004242
2020-06-12 18:45:45,224 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.130492091178894
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Steps = 74000/278576
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - dev_loss = 0.123426 || dev_eval_scores = {'perplexity': 1.1313656568527222}
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO - train_loss = 0.15936923027038574
2020-06-12 18:52:56,441 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:00:08,504 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:00:11,867 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=4756
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1283477544784546
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:00:11,881 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:00:11,882 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 19:00:11,882 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:00:11,882 - crisis_transformers.trainer - INFO - Steps = 74400/278576
2020-06-12 19:00:11,882 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:00:11,882 - crisis_transformers.trainer - INFO - dev_loss = 0.120754 || dev_eval_scores = {'perplexity': 1.1283477544784546}
2020-06-12 19:00:11,898 - crisis_transformers.trainer - INFO - train_loss = 0.15900550782680511
2020-06-12 19:00:11,898 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1283477544784546
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Steps = 74800/278576
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:07:24,081 - crisis_transformers.trainer - INFO - dev_loss = 0.122012 || dev_eval_scores = {'perplexity': 1.1297677755355835}
2020-06-12 19:07:24,082 - crisis_transformers.trainer - INFO - train_loss = 0.15857523679733276
2020-06-12 19:07:24,082 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:14:35,509 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:14:38,680 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=5556
2020-06-12 19:14:38,690 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:14:38,690 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:14:38,690 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:14:38,690 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 19:14:38,690 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:14:38,690 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1280550956726074
2020-06-12 19:14:38,691 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:14:38,691 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:14:38,691 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:14:38,691 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 19:14:38,691 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:14:38,691 - crisis_transformers.trainer - INFO - Steps = 75200/278576
2020-06-12 19:14:38,692 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:14:38,692 - crisis_transformers.trainer - INFO - dev_loss = 0.120495 || dev_eval_scores = {'perplexity': 1.1280550956726074}
2020-06-12 19:14:38,709 - crisis_transformers.trainer - INFO - train_loss = 0.15801657736301422
2020-06-12 19:14:38,709 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:21:51,621 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:21:51,621 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1280550956726074
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Steps = 75600/278576
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:21:51,622 - crisis_transformers.trainer - INFO - dev_loss = 0.120551 || dev_eval_scores = {'perplexity': 1.1281187534332275}
2020-06-12 19:21:51,623 - crisis_transformers.trainer - INFO - train_loss = 0.15759296715259552
2020-06-12 19:21:51,623 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:29:02,897 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:29:06,248 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=6356
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.126711368560791
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:29:06,257 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:29:06,258 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 19:29:06,258 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:29:06,258 - crisis_transformers.trainer - INFO - Steps = 76000/278576
2020-06-12 19:29:06,259 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:29:06,259 - crisis_transformers.trainer - INFO - dev_loss = 0.119303 || dev_eval_scores = {'perplexity': 1.126711368560791}
2020-06-12 19:29:06,271 - crisis_transformers.trainer - INFO - train_loss = 0.15713545680046082
2020-06-12 19:29:06,271 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:36:18,058 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:36:21,263 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=6756
2020-06-12 19:36:21,270 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:36:21,270 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:36:21,270 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:36:21,271 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 19:36:21,271 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:36:21,271 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1253490447998047
2020-06-12 19:36:21,271 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:36:21,271 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:36:21,271 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:36:21,272 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 19:36:21,272 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:36:21,272 - crisis_transformers.trainer - INFO - Steps = 76400/278576
2020-06-12 19:36:21,272 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:36:21,272 - crisis_transformers.trainer - INFO - dev_loss = 0.118093 || dev_eval_scores = {'perplexity': 1.1253490447998047}
2020-06-12 19:36:21,285 - crisis_transformers.trainer - INFO - train_loss = 0.15685245394706726
2020-06-12 19:36:21,285 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:43:33,123 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:43:36,558 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=7156
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1248881816864014
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:43:36,573 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:43:36,574 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 19:43:36,574 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:43:36,574 - crisis_transformers.trainer - INFO - Steps = 76800/278576
2020-06-12 19:43:36,574 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:43:36,574 - crisis_transformers.trainer - INFO - dev_loss = 0.117684 || dev_eval_scores = {'perplexity': 1.1248881816864014}
2020-06-12 19:43:36,592 - crisis_transformers.trainer - INFO - train_loss = 0.15634950995445251
2020-06-12 19:43:36,592 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1248881816864014
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Steps = 77200/278576
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:50:48,591 - crisis_transformers.trainer - INFO - dev_loss = 0.117770 || dev_eval_scores = {'perplexity': 1.1249850988388062}
2020-06-12 19:50:48,592 - crisis_transformers.trainer - INFO - train_loss = 0.1558857262134552
2020-06-12 19:50:48,592 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 19:58:00,383 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:58:03,711 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=7956
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1242866516113281
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 19:58:03,725 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 19:58:03,726 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 19:58:03,726 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 19:58:03,726 - crisis_transformers.trainer - INFO - Steps = 77600/278576
2020-06-12 19:58:03,726 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 19:58:03,726 - crisis_transformers.trainer - INFO - dev_loss = 0.117149 || dev_eval_scores = {'perplexity': 1.1242866516113281}
2020-06-12 19:58:03,742 - crisis_transformers.trainer - INFO - train_loss = 0.15545228123664856
2020-06-12 19:58:03,742 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:05:15,952 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:05:19,295 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=8356
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1240224838256836
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:05:19,307 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:05:19,308 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 20:05:19,308 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:05:19,308 - crisis_transformers.trainer - INFO - Steps = 78000/278576
2020-06-12 20:05:19,308 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:05:19,308 - crisis_transformers.trainer - INFO - dev_loss = 0.116914 || dev_eval_scores = {'perplexity': 1.1240224838256836}
2020-06-12 20:05:19,322 - crisis_transformers.trainer - INFO - train_loss = 0.15514682233333588
2020-06-12 20:05:19,322 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:12:30,593 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:12:33,718 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=8756
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1232761144638062
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:12:33,729 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:12:33,730 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 20:12:33,730 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:12:33,730 - crisis_transformers.trainer - INFO - Steps = 78400/278576
2020-06-12 20:12:33,730 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:12:33,730 - crisis_transformers.trainer - INFO - dev_loss = 0.116250 || dev_eval_scores = {'perplexity': 1.1232761144638062}
2020-06-12 20:12:33,744 - crisis_transformers.trainer - INFO - train_loss = 0.15461046993732452
2020-06-12 20:12:33,744 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:19:45,605 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1232761144638062
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Steps = 78800/278576
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - dev_loss = 0.117339 || dev_eval_scores = {'perplexity': 1.12450110912323}
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO - train_loss = 0.15414145588874817
2020-06-12 20:19:45,606 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:26:57,592 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:27:00,603 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=9556
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1222569942474365
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:27:00,617 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:27:00,618 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 20:27:00,618 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:27:00,618 - crisis_transformers.trainer - INFO - Steps = 79200/278576
2020-06-12 20:27:00,618 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:27:00,618 - crisis_transformers.trainer - INFO - dev_loss = 0.115342 || dev_eval_scores = {'perplexity': 1.1222569942474365}
2020-06-12 20:27:00,635 - crisis_transformers.trainer - INFO - train_loss = 0.15376870334148407
2020-06-12 20:27:00,635 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:34:13,086 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=9956
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1214654445648193
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:34:16,742 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:34:16,743 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 20:34:16,743 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:34:16,743 - crisis_transformers.trainer - INFO - Steps = 79600/278576
2020-06-12 20:34:16,743 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:34:16,743 - crisis_transformers.trainer - INFO - dev_loss = 0.114636 || dev_eval_scores = {'perplexity': 1.1214654445648193}
2020-06-12 20:34:16,745 - crisis_transformers.trainer - INFO - train_loss = 0.1534395068883896
2020-06-12 20:34:16,745 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1214654445648193
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Steps = 80000/278576
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - dev_loss = 0.114919 || dev_eval_scores = {'perplexity': 1.1217821836471558}
2020-06-12 20:41:28,720 - crisis_transformers.trainer - INFO - train_loss = 0.15301528573036194
2020-06-12 20:41:28,721 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:48:40,263 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1214654445648193
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Steps = 80400/278576
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - dev_loss = 0.116439 || dev_eval_scores = {'perplexity': 1.123489499092102}
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO - train_loss = 0.1526806503534317
2020-06-12 20:48:40,265 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 20:55:51,280 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:55:54,387 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=11156
2020-06-12 20:55:54,402 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1208057403564453
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 20:55:54,403 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 20:55:54,404 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 20:55:54,404 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 20:55:54,404 - crisis_transformers.trainer - INFO - Steps = 80800/278576
2020-06-12 20:55:54,404 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 20:55:54,404 - crisis_transformers.trainer - INFO - dev_loss = 0.114048 || dev_eval_scores = {'perplexity': 1.1208057403564453}
2020-06-12 20:55:54,422 - crisis_transformers.trainer - INFO - train_loss = 0.15231111645698547
2020-06-12 20:55:54,422 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1208057403564453
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 21:03:06,140 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:03:06,141 - crisis_transformers.trainer - INFO - Steps = 81200/278576
2020-06-12 21:03:06,141 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:03:06,141 - crisis_transformers.trainer - INFO - dev_loss = 0.114643 || dev_eval_scores = {'perplexity': 1.1214734315872192}
2020-06-12 21:03:06,141 - crisis_transformers.trainer - INFO - train_loss = 0.15194369852542877
2020-06-12 21:03:06,141 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:10:17,767 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:10:20,890 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=11956
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1198288202285767
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:10:20,897 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:10:20,898 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 21:10:20,898 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:10:20,898 - crisis_transformers.trainer - INFO - Steps = 81600/278576
2020-06-12 21:10:20,898 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:10:20,898 - crisis_transformers.trainer - INFO - dev_loss = 0.113176 || dev_eval_scores = {'perplexity': 1.1198288202285767}
2020-06-12 21:10:20,900 - crisis_transformers.trainer - INFO - train_loss = 0.15155275166034698
2020-06-12 21:10:20,900 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:17:33,024 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:17:36,142 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=12356
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1191425323486328
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:17:36,143 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:17:36,144 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 21:17:36,144 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:17:36,144 - crisis_transformers.trainer - INFO - Steps = 82000/278576
2020-06-12 21:17:36,144 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:17:36,144 - crisis_transformers.trainer - INFO - dev_loss = 0.112563 || dev_eval_scores = {'perplexity': 1.1191425323486328}
2020-06-12 21:17:36,151 - crisis_transformers.trainer - INFO - train_loss = 0.15120427310466766
2020-06-12 21:17:36,151 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1191425323486328
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Steps = 82400/278576
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - dev_loss = 0.113121 || dev_eval_scores = {'perplexity': 1.1197669506072998}
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO - train_loss = 0.1508565992116928
2020-06-12 21:24:48,557 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:32:00,891 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:32:00,893 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:32:00,893 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:32:00,893 - crisis_transformers.trainer - INFO - Early stop count = 2/20
2020-06-12 21:32:00,893 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1191425323486328
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 12s
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Steps = 82800/278576
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - dev_loss = 0.114633 || dev_eval_scores = {'perplexity': 1.1214618682861328}
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO - train_loss = 0.15052178502082825
2020-06-12 21:32:00,894 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Early stop count = 3/20
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1191425323486328
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 11s
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Steps = 83200/278576
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - dev_loss = 0.112780 || dev_eval_scores = {'perplexity': 1.1193852424621582}
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO - train_loss = 0.15016387403011322
2020-06-12 21:39:11,977 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:46:23,357 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:46:26,472 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=13956
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1182266473770142
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:46:26,487 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:46:26,489 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 21:46:26,489 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:46:26,489 - crisis_transformers.trainer - INFO - Steps = 83600/278576
2020-06-12 21:46:26,489 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:46:26,489 - crisis_transformers.trainer - INFO - dev_loss = 0.111744 || dev_eval_scores = {'perplexity': 1.1182266473770142}
2020-06-12 21:46:26,507 - crisis_transformers.trainer - INFO - train_loss = 0.14978548884391785
2020-06-12 21:46:26,507 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 21:53:38,893 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:53:42,051 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=14356
2020-06-12 21:53:42,053 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 21:53:42,053 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 21:53:42,053 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 21:53:42,053 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 21:53:42,053 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1176480054855347
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Steps = 84000/278576
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 21:53:42,054 - crisis_transformers.trainer - INFO - dev_loss = 0.111226 || dev_eval_scores = {'perplexity': 1.1176480054855347}
2020-06-12 21:53:42,056 - crisis_transformers.trainer - INFO - train_loss = 0.1494358777999878
2020-06-12 21:53:42,056 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 22:00:52,990 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:00:56,106 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=14756
2020-06-12 22:00:56,119 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 22:00:56,119 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:00:56,119 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 22:00:56,119 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 22:00:56,119 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 22:00:56,120 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1175894737243652
2020-06-12 22:00:56,120 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 22:00:56,120 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 22:00:56,120 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 22:00:56,121 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 22:00:56,121 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 22:00:56,121 - crisis_transformers.trainer - INFO - Steps = 84400/278576
2020-06-12 22:00:56,121 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 22:00:56,121 - crisis_transformers.trainer - INFO - dev_loss = 0.111174 || dev_eval_scores = {'perplexity': 1.1175894737243652}
2020-06-12 22:00:56,136 - crisis_transformers.trainer - INFO - train_loss = 0.14908182621002197
2020-06-12 22:00:56,136 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 22:08:09,602 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 22:08:09,602 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:08:09,602 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 22:08:09,602 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 22:08:09,602 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 22:08:09,602 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1175894737243652
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 13s
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Steps = 84800/278576
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 22:08:09,603 - crisis_transformers.trainer - INFO - dev_loss = 0.111978 || dev_eval_scores = {'perplexity': 1.1184886693954468}
2020-06-12 22:08:09,604 - crisis_transformers.trainer - INFO - train_loss = 0.1487855762243271
2020-06-12 22:08:09,604 - crisis_transformers.trainer - INFO -
********************************************
2020-06-12 22:15:29,618 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:15:33,237 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=15556
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1161783933639526
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 22:15:33,238 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 22:15:33,240 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 23s
2020-06-12 22:15:33,240 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 22:15:33,240 - crisis_transformers.trainer - INFO - Steps = 85200/278576
2020-06-12 22:15:33,240 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 22:15:33,240 - crisis_transformers.trainer - INFO - dev_loss = 0.109911 || dev_eval_scores = {'perplexity': 1.1161783933639526}
2020-06-12 22:15:33,242 - crisis_transformers.trainer - INFO - train_loss = 0.14848528802394867
2020-06-12 22:15:33,242 - crisis_transformers.trainer - INFO -
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2020-06-12 22:22:49,305 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Early stop count = 1/20
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1161783933639526
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 16s
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Steps = 85600/278576
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - dev_loss = 0.110636 || dev_eval_scores = {'perplexity': 1.1169886589050293}
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO - train_loss = 0.14812599122524261
2020-06-12 22:22:49,306 - crisis_transformers.trainer - INFO -
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2020-06-12 22:30:01,038 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:30:04,724 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=16356
2020-06-12 22:30:04,730 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 22:30:04,730 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:30:04,730 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 22:30:04,730 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 22:30:04,730 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1152490377426147
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 15s
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Steps = 86000/278576
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 22:30:04,731 - crisis_transformers.trainer - INFO - dev_loss = 0.109078 || dev_eval_scores = {'perplexity': 1.1152490377426147}
2020-06-12 22:30:04,747 - crisis_transformers.trainer - INFO - train_loss = 0.14784550666809082
2020-06-12 22:30:04,747 - crisis_transformers.trainer - INFO -
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2020-06-12 22:37:16,018 - crisis_transformers.trainer - INFO - Save model to tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:37:19,119 - crisis_transformers.trainer - INFO - Save check-point at epoch=4 step=16756
2020-06-12 22:37:19,119 - crisis_transformers.trainer - INFO - ***** Evaluation report *****
2020-06-12 22:37:19,119 - crisis_transformers.trainer - INFO - Output path (short): tmp/gpt2_medium_for_source_code_code_generate
2020-06-12 22:37:19,119 - crisis_transformers.trainer - INFO - Early stop on: perplexity
2020-06-12 22:37:19,119 - crisis_transformers.trainer - INFO - Early stop count = 0/20
2020-06-12 22:37:19,119 - crisis_transformers.trainer - INFO - Eval steps = 400 or (iterations = 400)
2020-06-12 22:37:19,120 - crisis_transformers.trainer - INFO - Best score (perplexity) = -1.1139332056045532
2020-06-12 22:37:19,120 - crisis_transformers.trainer - INFO - Gradient Accumulation steps = 1
2020-06-12 22:37:19,120 - crisis_transformers.trainer - INFO - Num of training examples (actually no. of iterations per epoch for Iterable Dataset) = 69642
2020-06-12 22:37:19,120 - crisis_transformers.trainer - INFO - Num of development examples (actually no. of iterations per epoch for Iterable Dataset) = 7738
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO - Time spent since last evaluation = 0h 7m 14s
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO - Epoch = 5/16
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO - Steps = 86400/278576
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO - Instantaneous batch size per GPU = 2 and n_gpu = 2 so the input batch size = 4
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO - dev_loss = 0.107897 || dev_eval_scores = {'perplexity': 1.1139332056045532}
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO - train_loss = 0.14752434194087982
2020-06-12 22:37:19,121 - crisis_transformers.trainer - INFO -
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