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--- |
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base_model: dmis-lab/biobert-base-cased-v1.2 |
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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: devicebert-base-cased-v1.0 |
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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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# devicebert-base-cased-v1.0 |
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This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Precision: 0.9360 |
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- Recall: 0.9301 |
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- F1: 0.9330 |
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- Accuracy: 0.9700 |
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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: 1e-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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### 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 | 81 | nan | 0.9360 | 0.9301 | 0.9330 | 0.9700 | |
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| No log | 2.0 | 162 | nan | 0.9226 | 0.9343 | 0.9284 | 0.9709 | |
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| No log | 3.0 | 243 | nan | 0.9244 | 0.9322 | 0.9283 | 0.9690 | |
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| No log | 4.0 | 324 | nan | 0.9319 | 0.9280 | 0.9299 | 0.9709 | |
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| No log | 5.0 | 405 | nan | 0.9323 | 0.9343 | 0.9333 | 0.9719 | |
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| No log | 6.0 | 486 | nan | 0.9375 | 0.9216 | 0.9295 | 0.9672 | |
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| 0.0708 | 7.0 | 567 | nan | 0.9421 | 0.9301 | 0.9360 | 0.9709 | |
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| 0.0708 | 8.0 | 648 | nan | 0.9358 | 0.9258 | 0.9308 | 0.9709 | |
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| 0.0708 | 9.0 | 729 | nan | 0.9359 | 0.9280 | 0.9319 | 0.9709 | |
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| 0.0708 | 10.0 | 810 | nan | 0.9375 | 0.9216 | 0.9295 | 0.9700 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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