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update model card README.md

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@@ -3,17 +3,20 @@ license: apache-2.0
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  tags:
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  - generated_from_trainer
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  datasets:
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- - billsum
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  model-index:
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  - name: t5-small-medicalnews-summarization
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  results: []
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  ---
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- This model is not completed yet
 
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  # t5-small-medicalnews-summarization
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- This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
 
 
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  ## Model description
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@@ -32,7 +35,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -45,12 +48,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 62 | 3.1698 |
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  ### Framework versions
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- - Transformers 4.20.1
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  - Pytorch 1.12.0+cu113
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  - Datasets 2.4.0
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  - Tokenizers 0.12.1
 
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  tags:
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  - generated_from_trainer
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  datasets:
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+ - cnn_dailymail
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  model-index:
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  - name: t5-small-medicalnews-summarization
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  results: []
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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-medicalnews-summarization
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+ This model is a fine-tuned version of [weijiahaha/t5-small-medicalnews-summarization](https://huggingface.co/weijiahaha/t5-small-medicalnews-summarization) on the cnn_dailymail dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6477
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.9195 | 1.0 | 718 | 1.6477 |
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  ### Framework versions
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+ - Transformers 4.21.1
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  - Pytorch 1.12.0+cu113
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  - Datasets 2.4.0
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  - Tokenizers 0.12.1