| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| datasets: |
| - snli |
| metrics: |
| - rouge |
| model-index: |
| - name: t5-small-finetuned-contradiction |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| dataset: |
| name: snli |
| type: snli |
| args: plain_text |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 34.4237 |
| --- |
| |
| <!-- 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. --> |
|
|
| # t5-small-finetuned-contradiction |
|
|
| This model is a fine-tuned version of [domenicrosati/t5-small-finetuned-contradiction](https://huggingface.co/domenicrosati/t5-small-finetuned-contradiction) on the snli dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.0458 |
| - Rouge1: 34.4237 |
| - Rouge2: 14.5442 |
| - Rougel: 32.5483 |
| - Rougelsum: 32.5785 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5.6e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | 1.8605 | 1.0 | 2863 | 2.0813 | 34.4597 | 14.5186 | 32.6909 | 32.7097 | |
| | 1.9209 | 2.0 | 5726 | 2.0721 | 34.3859 | 14.5733 | 32.5188 | 32.5524 | |
| | 1.9367 | 3.0 | 8589 | 2.0623 | 34.4192 | 14.455 | 32.581 | 32.5962 | |
| | 1.9539 | 4.0 | 11452 | 2.0565 | 34.5148 | 14.6131 | 32.6786 | 32.7174 | |
| | 1.9655 | 5.0 | 14315 | 2.0538 | 34.4393 | 14.6439 | 32.6344 | 32.6587 | |
| | 1.9683 | 6.0 | 17178 | 2.0493 | 34.7199 | 14.7763 | 32.8625 | 32.8782 | |
| | 1.9735 | 7.0 | 20041 | 2.0476 | 34.5366 | 14.6362 | 32.6939 | 32.7177 | |
| | 1.98 | 8.0 | 22904 | 2.0458 | 34.5 | 14.5695 | 32.6219 | 32.6478 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.11.0+cu102 |
| - Datasets 2.1.0 |
| - Tokenizers 0.12.1 |
|
|
