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--- |
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license: apache-2.0 |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- snli |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-contradiction |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: snli |
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type: snli |
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args: plain_text |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 34.4237 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# t5-small-finetuned-contradiction |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0458 |
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- Rouge1: 34.4237 |
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- Rouge2: 14.5442 |
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- Rougel: 32.5483 |
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- Rougelsum: 32.5785 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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: 8 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 1.8605 | 1.0 | 2863 | 2.0813 | 34.4597 | 14.5186 | 32.6909 | 32.7097 | |
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| 1.9209 | 2.0 | 5726 | 2.0721 | 34.3859 | 14.5733 | 32.5188 | 32.5524 | |
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| 1.9367 | 3.0 | 8589 | 2.0623 | 34.4192 | 14.455 | 32.581 | 32.5962 | |
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| 1.9539 | 4.0 | 11452 | 2.0565 | 34.5148 | 14.6131 | 32.6786 | 32.7174 | |
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| 1.9655 | 5.0 | 14315 | 2.0538 | 34.4393 | 14.6439 | 32.6344 | 32.6587 | |
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| 1.9683 | 6.0 | 17178 | 2.0493 | 34.7199 | 14.7763 | 32.8625 | 32.8782 | |
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| 1.9735 | 7.0 | 20041 | 2.0476 | 34.5366 | 14.6362 | 32.6939 | 32.7177 | |
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| 1.98 | 8.0 | 22904 | 2.0458 | 34.5 | 14.5695 | 32.6219 | 32.6478 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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