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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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model-index: |
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- name: bart-finetuned-pubmed |
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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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# bart-finetuned-pubmed |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5363 |
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- Rouge2 Precision: 0.3459 |
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- Rouge2 Recall: 0.2455 |
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- Rouge2 Fmeasure: 0.2731 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
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| 1.652 | 1.0 | 1125 | 1.5087 | 0.3647 | 0.2425 | 0.2772 | |
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| 1.4695 | 2.0 | 2250 | 1.5039 | 0.3448 | 0.2457 | 0.2732 | |
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| 1.3714 | 3.0 | 3375 | 1.4842 | 0.3509 | 0.2474 | 0.277 | |
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| 1.2734 | 4.0 | 4500 | 1.4901 | 0.3452 | 0.2426 | 0.2716 | |
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| 1.1853 | 5.0 | 5625 | 1.5152 | 0.3658 | 0.2371 | 0.2744 | |
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| 1.0975 | 6.0 | 6750 | 1.5133 | 0.3529 | 0.2417 | 0.2729 | |
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| 1.0448 | 7.0 | 7875 | 1.5203 | 0.3485 | 0.2464 | 0.275 | |
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| 0.9999 | 8.0 | 9000 | 1.5316 | 0.3437 | 0.2435 | 0.2719 | |
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| 0.9732 | 9.0 | 10125 | 1.5338 | 0.3464 | 0.2446 | 0.2732 | |
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| 0.954 | 10.0 | 11250 | 1.5363 | 0.3459 | 0.2455 | 0.2731 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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