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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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- generated_from_trainer
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datasets:
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- pubmed-summarization
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metrics:
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- rouge
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model-index:
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- name: my_awesome_billsum_model
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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: pubmed-summarization
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type: pubmed-summarization
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config: section
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split: test
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args: section
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metrics:
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- name: Rouge1
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type: rouge
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value: 0.1393
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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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# my_awesome_billsum_model
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the pubmed-summarization dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3423
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- Rouge1: 0.1393
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- Rouge2: 0.0556
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- Rougel: 0.1172
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- Rougelsum: 0.1172
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- Gen Len: 19.0
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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: 2e-05
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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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- 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: 2
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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 | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| No log | 1.0 | 375 | 2.3755 | 0.1375 | 0.0538 | 0.1159 | 0.1159 | 19.0 |
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| 2.6739 | 2.0 | 750 | 2.3423 | 0.1393 | 0.0556 | 0.1172 | 0.1172 | 19.0 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.1+cu116
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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