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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-mlm-pubmed-35 |
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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-mlm-pubmed-35 |
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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: 0.9359 |
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- Rouge2 Precision: 0.5451 |
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- Rouge2 Recall: 0.4232 |
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- Rouge2 Fmeasure: 0.4666 |
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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: 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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| 1.4156 | 1.0 | 663 | 1.0366 | 0.5165 | 0.3967 | 0.4394 | |
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| 1.1773 | 2.0 | 1326 | 0.9841 | 0.5354 | 0.4168 | 0.4589 | |
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| 1.0894 | 3.0 | 1989 | 0.9554 | 0.5346 | 0.4133 | 0.4563 | |
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| 0.9359 | 4.0 | 2652 | 0.9440 | 0.5357 | 0.4163 | 0.4587 | |
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| 0.8758 | 5.0 | 3315 | 0.9340 | 0.5428 | 0.4226 | 0.465 | |
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| 0.8549 | 6.0 | 3978 | 0.9337 | 0.5385 | 0.422 | 0.4634 | |
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| 0.7743 | 7.0 | 4641 | 0.9330 | 0.542 | 0.422 | 0.4647 | |
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| 0.7465 | 8.0 | 5304 | 0.9315 | 0.5428 | 0.4231 | 0.4654 | |
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| 0.7348 | 9.0 | 5967 | 0.9344 | 0.5462 | 0.4244 | 0.4674 | |
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| 0.7062 | 10.0 | 6630 | 0.9359 | 0.5451 | 0.4232 | 0.4666 | |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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