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README.md CHANGED
@@ -19,15 +19,15 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6378
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- - Rouge1: 0.4698
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- - Rouge2: 0.2197
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- - Rougel: 0.385
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- - Rougelsum: 0.3849
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- - Gen Len: 26.5251
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- - Precision: 0.9107
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- - Recall: 0.909
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- - F1: 0.9096
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  ## Model description
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@@ -54,7 +54,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 16
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -72,11 +72,15 @@ The following hyperparameters were used during training:
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  | 1.7559 | 9.0 | 3511 | 0.9086 | 26.424 | 1.6662 | 0.9098 | 0.9078 | 0.4632 | 0.215 | 0.38 | 0.3799 |
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  | 1.7559 | 10.0 | 3902 | 0.9089 | 26.5425 | 1.6594 | 0.9099 | 0.9082 | 0.4651 | 0.2168 | 0.3812 | 0.3812 |
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  | 1.7357 | 11.0 | 4293 | 0.9091 | 26.6051 | 1.6555 | 0.91 | 0.9086 | 0.4663 | 0.2178 | 0.3824 | 0.3823 |
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- | 1.7297 | 12.0 | 4680 | 1.6508 | 0.4668 | 0.2175 | 0.3823 | 0.3822 | 26.4393| 0.9103 | 0.9084 | 0.9092 |
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- | 1.7165 | 13.0 | 5071 | 1.6451 | 0.4687 | 0.2191 | 0.3834 | 0.3834 | 26.6385| 0.9103 | 0.9089 | 0.9094 |
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- | 1.7165 | 14.0 | 5462 | 1.6405 | 0.4691 | 0.2193 | 0.3845 | 0.3844 | 26.4156| 0.9106 | 0.9087 | 0.9095 |
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- | 1.7068 | 15.0 | 5853 | 1.6383 | 0.4699 | 0.2204 | 0.3853 | 0.3853 | 26.4571| 0.9108 | 0.9089 | 0.9097 |
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- | 1.7004 | 15.99 | 6240 | 1.6378 | 0.4698 | 0.2197 | 0.385 | 0.3849 | 26.5251| 0.9107 | 0.909 | 0.9096 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6258
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+ - Rouge1: 0.4708
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+ - Rouge2: 0.2214
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+ - Rougel: 0.3861
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+ - Rougelsum: 0.3863
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+ - Gen Len: 26.5411
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+ - Precision: 0.9108
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+ - Recall: 0.9093
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+ - F1: 0.9099
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  ## Model description
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  - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 20
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  | 1.7559 | 9.0 | 3511 | 0.9086 | 26.424 | 1.6662 | 0.9098 | 0.9078 | 0.4632 | 0.215 | 0.38 | 0.3799 |
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  | 1.7559 | 10.0 | 3902 | 0.9089 | 26.5425 | 1.6594 | 0.9099 | 0.9082 | 0.4651 | 0.2168 | 0.3812 | 0.3812 |
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  | 1.7357 | 11.0 | 4293 | 0.9091 | 26.6051 | 1.6555 | 0.91 | 0.9086 | 0.4663 | 0.2178 | 0.3824 | 0.3823 |
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+ | 1.7297 | 12.0 | 4680 | 0.9092 | 26.4393 | 1.6508 | 0.9103 | 0.9084 | 0.4668 | 0.2175 | 0.3823 | 0.3822 |
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+ | 1.7165 | 13.0 | 5071 | 0.9094 | 26.6385 | 1.6451 | 0.9103 | 0.9089 | 0.4687 | 0.2191 | 0.3834 | 0.3834 |
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+ | 1.7165 | 14.0 | 5462 | 0.9095 | 26.4156 | 1.6405 | 0.9106 | 0.9087 | 0.4691 | 0.2193 | 0.3845 | 0.3844 |
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+ | 1.7068 | 15.0 | 5853 | 0.9097 | 26.4571 | 1.6383 | 0.9108 | 0.9089 | 0.4699 | 0.2204 | 0.3853 | 0.3853 |
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+ | 1.7004 | 16.0 | 6240 | 1.6346 | 0.4703 | 0.2204 | 0.385 | 0.385 | 26.4247| 0.9108 | 0.9089 | 0.9097 |
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+ | 1.6923 | 17.0 | 6631 | 1.6305 | 0.4706 | 0.221 | 0.3855 | 0.3856 | 26.4436| 0.911 | 0.9091 | 0.9099 |
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+ | 1.6839 | 18.0 | 7022 | 1.6285 | 0.4712 | 0.2215 | 0.3862 | 0.3864 | 26.612 | 0.9106 | 0.9094 | 0.9098 |
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+ | 1.6839 | 19.0 | 7413 | 1.6263 | 0.4709 | 0.2217 | 0.3862 | 0.3864 | 26.5291| 0.9108 | 0.9093 | 0.9099 |
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+ | 1.6743 | 19.99 | 7800 | 1.6258 | 0.4708 | 0.2214 | 0.3861 | 0.3863 | 26.5411| 0.9108 | 0.9093 | 0.9099 |
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  ### Framework versions
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