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update model card README.md

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+ ---
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+ license: mit
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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: bart-finetuned-summarization-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: pubmed-summarization
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+ type: pubmed-summarization
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+ config: section
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+ split: validation
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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: 43.1219
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+ ---
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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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+
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+ # bart-finetuned-summarization-pubmed
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+
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+ This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the pubmed-summarization dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7193
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+ - Rouge1: 43.1219
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+ - Rouge2: 18.7311
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+ - Rougel: 28.1006
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+ - Rougelsum: 38.0914
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+ - Gen Len: 128.6263
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 10
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+ - eval_batch_size: 10
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+ - seed: 42
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+ - gradient_accumulation_steps: 5
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+ - total_train_batch_size: 50
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
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+ | 1.8564 | 1.0 | 2398 | 1.7437 | 43.2294 | 18.867 | 28.2156 | 38.1868 | 128.4766 |
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+ | 1.75 | 2.0 | 4796 | 1.7193 | 43.1219 | 18.7311 | 28.1006 | 38.0914 | 128.6263 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3