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bart-email-multitask

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bart
text2text-generation
Generated from Trainer
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rosypossyyyy commited on
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1 Parent(s): 8551d0d

Update: Added sender_name context to input format (From: sender)

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  1. README.md +19 -21
  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [rosypossyyyy/bart-email-multitask](https://huggingface.co/rosypossyyyy/bart-email-multitask) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5796
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- - Rouge1: 50.71
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- - Rouge2: 36.15
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- - Rougel: 44.19
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- - Rougelsum: 44.64
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- - Gen Len: 53.1399
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  ## Model description
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@@ -41,7 +41,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
@@ -49,7 +49,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 16
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_steps: 500
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  - num_epochs: 2
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | 0.3147 | 0.1726 | 500 | 0.7136 | 48.61 | 33.86 | 41.59 | 42.19 | 57.5974 |
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- | 0.3772 | 0.3452 | 1000 | 0.6479 | 49.95 | 35.09 | 43.0 | 43.46 | 53.2927 |
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- | 0.5262 | 0.5178 | 1500 | 0.5853 | 49.93 | 35.72 | 43.48 | 43.95 | 55.0490 |
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- | 0.5042 | 0.6904 | 2000 | 0.5738 | 50.6 | 35.79 | 43.75 | 44.21 | 52.4930 |
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- | 0.4835 | 0.8630 | 2500 | 0.5613 | 50.53 | 36.13 | 43.77 | 44.27 | 53.9771 |
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- | 0.4328 | 1.0356 | 3000 | 0.5497 | 50.83 | 36.42 | 44.37 | 44.83 | 52.4157 |
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- | 0.4392 | 1.2082 | 3500 | 0.5716 | 51.0 | 36.64 | 44.45 | 44.93 | 53.0539 |
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- | 0.4162 | 1.3808 | 4000 | 0.5490 | 50.78 | 36.5 | 44.25 | 44.76 | 53.1325 |
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- | 0.4235 | 1.5534 | 4500 | 0.5395 | 50.65 | 36.31 | 44.24 | 44.72 | 53.9557 |
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- | 0.408 | 1.7260 | 5000 | 0.5433 | 50.67 | 36.51 | 44.2 | 44.7 | 53.9173 |
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  ### Framework versions
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- - Transformers 4.57.3
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  - Pytorch 2.9.0+cu126
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- - Datasets 4.0.0
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- - Tokenizers 0.22.1
 
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  This model is a fine-tuned version of [rosypossyyyy/bart-email-multitask](https://huggingface.co/rosypossyyyy/bart-email-multitask) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5448
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+ - Rouge1: 51.01
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+ - Rouge2: 36.53
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+ - Rougel: 44.46
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+ - Rougelsum: 44.91
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+ - Gen Len: 53.5864
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
 
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  - total_train_batch_size: 16
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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  - num_epochs: 2
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | 0.3719 | 0.1726 | 500 | 0.5641 | 49.82 | 35.56 | 43.37 | 43.9 | 55.6862 |
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+ | 0.39 | 0.3452 | 1000 | 0.5499 | 50.66 | 36.17 | 44.07 | 44.56 | 53.0616 |
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+ | 0.4325 | 0.5178 | 1500 | 0.5412 | 50.59 | 36.52 | 44.19 | 44.63 | 54.4194 |
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+ | 0.4328 | 0.6904 | 2000 | 0.5556 | 50.8 | 36.6 | 44.19 | 44.7 | 54.1698 |
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+ | 0.4133 | 0.8630 | 2500 | 0.5358 | 50.67 | 36.36 | 44.02 | 44.56 | 54.8808 |
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+ | 0.3576 | 1.0356 | 3000 | 0.5371 | 51.14 | 36.78 | 44.59 | 45.09 | 53.4543 |
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+ | 0.3878 | 1.2082 | 3500 | 0.5359 | 50.77 | 36.52 | 44.17 | 44.73 | 54.4243 |
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+ | 0.3757 | 1.3808 | 4000 | 0.5294 | 50.76 | 36.73 | 44.34 | 44.9 | 54.2312 |
 
 
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  ### Framework versions
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+ - Transformers 4.57.5
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  - Pytorch 2.9.0+cu126
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+ - Datasets 4.5.0
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+ - Tokenizers 0.22.2
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