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--- |
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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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model-index: |
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- name: NLPGroupProject-Finetune-BioBert |
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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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# NLPGroupProject-Finetune-BioBert |
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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: 1.3977 |
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- Accuracy: 0.717 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.25 | 250 | 0.7935 | 0.706 | |
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| 0.8891 | 0.5 | 500 | 0.7591 | 0.718 | |
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| 0.8891 | 0.75 | 750 | 1.0569 | 0.713 | |
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| 0.8322 | 1.0 | 1000 | 0.7604 | 0.698 | |
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| 0.8322 | 1.25 | 1250 | 0.7878 | 0.713 | |
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| 0.5962 | 1.5 | 1500 | 0.9118 | 0.724 | |
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| 0.5962 | 1.75 | 1750 | 0.8485 | 0.723 | |
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| 0.5589 | 2.0 | 2000 | 0.8411 | 0.717 | |
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| 0.5589 | 2.25 | 2250 | 1.3105 | 0.721 | |
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| 0.2834 | 2.5 | 2500 | 1.4089 | 0.706 | |
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| 0.2834 | 2.75 | 2750 | 1.3467 | 0.718 | |
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| 0.2876 | 3.0 | 3000 | 1.3977 | 0.717 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu118 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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