| --- |
| 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: 34.3638 |
| --- |
| |
| <!-- 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: 2.1269 |
| - Rouge1: 34.3638 |
| - Rouge2: 14.7916 |
| - Rougel: 32.6308 |
| - Rougelsum: 32.6288 |
|
|
| ## 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: 4 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | 2.1984 | 1.0 | 2863 | 2.1556 | 34.4429 | 14.6791 | 32.5812 | 32.5896 | |
| | 2.2085 | 2.0 | 5726 | 2.1390 | 34.3719 | 14.731 | 32.5979 | 32.5949 | |
| | 2.188 | 3.0 | 8589 | 2.1302 | 34.4276 | 14.7191 | 32.62 | 32.6132 | |
| | 2.1768 | 4.0 | 11452 | 2.1269 | 34.4408 | 14.8235 | 32.7067 | 32.7065 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.11.0+cu102 |
| - Datasets 2.1.0 |
| - Tokenizers 0.12.1 |
|
|
