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--- |
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library_name: transformers |
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base_model: allenai/biomed_roberta_base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: BioMedRoBERTa-finetuned-valid-testing |
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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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# BioMedRoBERTa-finetuned-valid-testing |
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This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0920 |
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- Precision: 0.8179 |
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- Recall: 0.8236 |
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- F1: 0.8207 |
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- Accuracy: 0.9760 |
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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: 0.0002 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 417 | 0.1029 | 0.7906 | 0.7974 | 0.7940 | 0.9711 | |
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| 0.256 | 2.0 | 834 | 0.0807 | 0.8322 | 0.8077 | 0.8198 | 0.9772 | |
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| 0.0658 | 3.0 | 1251 | 0.0862 | 0.7913 | 0.8086 | 0.7999 | 0.9712 | |
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| 0.0448 | 4.0 | 1668 | 0.0871 | 0.8132 | 0.8151 | 0.8142 | 0.9768 | |
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| 0.0288 | 5.0 | 2085 | 0.0920 | 0.8179 | 0.8236 | 0.8207 | 0.9760 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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