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--- |
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library_name: transformers |
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base_model: dmis-lab/biobert-base-cased-v1.1 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ncbi_disease |
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metrics: |
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- f1 |
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model-index: |
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- name: biobert_finetuned_ncbi_disease |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: ncbi_disease |
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type: ncbi_disease |
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config: ncbi_disease |
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split: validation |
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args: ncbi_disease |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8376383763837638 |
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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_finetuned_ncbi_disease |
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This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the ncbi_disease dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0892 |
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- F1: 0.8376 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.9562 | 1.0 | 170 | 0.5053 | 0.0 | |
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| 0.3057 | 2.0 | 340 | 0.1515 | 0.4819 | |
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| 0.14 | 3.0 | 510 | 0.0960 | 0.6639 | |
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| 0.0865 | 4.0 | 680 | 0.0761 | 0.7515 | |
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| 0.0575 | 5.0 | 850 | 0.0725 | 0.7722 | |
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| 0.0418 | 6.0 | 1020 | 0.0730 | 0.7808 | |
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| 0.0297 | 7.0 | 1190 | 0.0741 | 0.8132 | |
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| 0.0211 | 8.0 | 1360 | 0.0745 | 0.8211 | |
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| 0.014 | 9.0 | 1530 | 0.0881 | 0.8285 | |
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| 0.0111 | 10.0 | 1700 | 0.0892 | 0.8376 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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