| --- |
| license: mit |
| base_model: microsoft/phi-2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: 0504LayerAnalysis31 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # 0504LayerAnalysis31 |
|
|
| This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1092 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
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| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0003 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine_with_restarts |
| - lr_scheduler_warmup_steps: 60 |
| - num_epochs: 3 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 2.7445 | 0.09 | 10 | 2.6015 | |
| | 2.3433 | 0.18 | 20 | 1.7482 | |
| | 1.2286 | 0.27 | 30 | 0.5531 | |
| | 0.4068 | 0.36 | 40 | 0.2940 | |
| | 0.2388 | 0.45 | 50 | 0.1832 | |
| | 0.1922 | 0.54 | 60 | 0.1407 | |
| | 0.1518 | 0.63 | 70 | 0.1263 | |
| | 0.1415 | 0.73 | 80 | 0.1206 | |
| | 0.1372 | 0.82 | 90 | 0.1196 | |
| | 0.1298 | 0.91 | 100 | 0.1149 | |
| | 0.1334 | 1.0 | 110 | 0.1143 | |
| | 0.13 | 1.09 | 120 | 0.1131 | |
| | 0.1306 | 1.18 | 130 | 0.1149 | |
| | 0.128 | 1.27 | 140 | 0.1125 | |
| | 0.1309 | 1.36 | 150 | 0.1118 | |
| | 0.1237 | 1.45 | 160 | 0.1124 | |
| | 0.1239 | 1.54 | 170 | 0.1104 | |
| | 0.1267 | 1.63 | 180 | 0.1095 | |
| | 0.1243 | 1.72 | 190 | 0.1172 | |
| | 0.1279 | 1.81 | 200 | 0.1093 | |
| | 0.1245 | 1.9 | 210 | 0.1100 | |
| | 0.1189 | 1.99 | 220 | 0.1098 | |
| | 0.1236 | 2.08 | 230 | 0.1101 | |
| | 0.1209 | 2.18 | 240 | 0.1094 | |
| | 0.1209 | 2.27 | 250 | 0.1089 | |
| | 0.1297 | 2.36 | 260 | 0.1087 | |
| | 0.1224 | 2.45 | 270 | 0.1086 | |
| | 0.1151 | 2.54 | 280 | 0.1092 | |
| | 0.1185 | 2.63 | 290 | 0.1096 | |
| | 0.1211 | 2.72 | 300 | 0.1092 | |
| | 0.1235 | 2.81 | 310 | 0.1092 | |
| | 0.1243 | 2.9 | 320 | 0.1092 | |
| | 0.1272 | 2.99 | 330 | 0.1092 | |
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| ### Framework versions |
|
|
| - Transformers 4.36.0.dev0 |
| - Pytorch 2.1.2+cu121 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
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|
