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--- |
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library_name: transformers |
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base_model: dmis-lab/biobert-v1.1 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: biobert-v1.1-finetuned-medmcqa-2024-11-25-T17-21-20 |
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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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# biobert-v1.1-finetuned-medmcqa-2024-11-25-T17-21-20 |
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This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2111 |
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- Accuracy: 0.5742 |
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- F1: 0.5753 |
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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: 0.000159 |
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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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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 0.7483 | 0.9939 | 142 | 0.9367 | 0.5613 | 0.5628 | |
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| 0.6026 | 1.9921 | 284 | 0.9227 | 0.5685 | 0.5693 | |
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| 0.3491 | 2.9904 | 426 | 1.2111 | 0.5742 | 0.5753 | |
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| 0.2135 | 3.9956 | 569 | 1.5260 | 0.5697 | 0.5704 | |
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| 0.114 | 4.9869 | 710 | 1.9557 | 0.5666 | 0.5672 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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