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update model card README.md
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README.md
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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: 34.2745
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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 [t5-small](https://huggingface.co/t5-small) on the snli dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1770
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- Rouge1: 34.2745
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- Rouge2: 14.6382
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- Rougel: 32.5159
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- Rougelsum: 32.519
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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: 1
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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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| 2.2392 | 1.0 | 2863 | 2.1770 | 34.3717 | 14.682 | 32.6218 | 32.6239 |
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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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