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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: 34.3503 |
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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: 2.0662 |
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- Rouge1: 34.3503 |
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- Rouge2: 14.671 |
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- Rougel: 32.5398 |
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- Rougelsum: 32.5331 |
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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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| 2.0071 | 1.0 | 2863 | 2.1018 | 34.4519 | 14.6277 | 32.6441 | 32.6415 | |
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| 2.0704 | 2.0 | 5726 | 2.0897 | 34.4688 | 14.7508 | 32.6253 | 32.6227 | |
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| 2.0738 | 3.0 | 8589 | 2.0808 | 34.4291 | 14.5548 | 32.6263 | 32.6384 | |
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| 2.0788 | 4.0 | 11452 | 2.0744 | 34.6759 | 14.842 | 32.8169 | 32.823 | |
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| 2.0781 | 5.0 | 14315 | 2.0714 | 34.4961 | 14.7307 | 32.6362 | 32.6378 | |
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| 2.0687 | 6.0 | 17178 | 2.0674 | 34.6406 | 14.8359 | 32.8403 | 32.8423 | |
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| 2.0627 | 7.0 | 20041 | 2.0671 | 34.526 | 14.6943 | 32.6919 | 32.694 | |
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| 2.0585 | 8.0 | 22904 | 2.0662 | 34.4196 | 14.7107 | 32.607 | 32.6035 | |
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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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