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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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- pub_med_summarization_dataset
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metrics:
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- rouge
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model-index:
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- name: bart-base-finetuned-pubmed
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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: pub_med_summarization_dataset
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type: pub_med_summarization_dataset
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args: document
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metrics:
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- name: Rouge1
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type: rouge
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value: 9.3963
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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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# bart-base-finetuned-pubmed
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the pub_med_summarization_dataset dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0277
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- Rouge1: 9.3963
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- Rouge2: 4.0473
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- Rougel: 8.4526
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- Rougelsum: 8.9659
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- Gen Len: 20.0
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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: 2
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- eval_batch_size: 2
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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: 5
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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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| 2.3706 | 1.0 | 4000 | 2.1245 | 9.1644 | 3.8264 | 8.2223 | 8.718 | 20.0 |
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| 2.2246 | 2.0 | 8000 | 2.0811 | 9.023 | 3.7716 | 8.1453 | 8.5998 | 20.0 |
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| 2.1034 | 3.0 | 12000 | 2.0469 | 9.4412 | 4.0783 | 8.4949 | 8.9977 | 20.0 |
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| 2.0137 | 4.0 | 16000 | 2.0390 | 9.2261 | 3.9307 | 8.3154 | 8.7937 | 20.0 |
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| 1.9288 | 5.0 | 20000 | 2.0277 | 9.3963 | 4.0473 | 8.4526 | 8.9659 | 20.0 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 1.10.0+cu111
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- Datasets 1.18.3
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- Tokenizers 0.11.6
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