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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 an unknown 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: 0.6816 |
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- Recall: 0.6691 |
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- F1: 0.6753 |
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- Accuracy: 0.8547 |
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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 | 101 | nan | 0.5981 | 0.5740 | 0.5858 | 0.8131 | |
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| No log | 2.0 | 202 | nan | 0.6673 | 0.6197 | 0.6427 | 0.8424 | |
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| No log | 3.0 | 303 | nan | 0.6926 | 0.6673 | 0.6797 | 0.8498 | |
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| No log | 4.0 | 404 | nan | 0.686 | 0.6271 | 0.6552 | 0.8473 | |
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| 0.3891 | 5.0 | 505 | nan | 0.6853 | 0.6490 | 0.6667 | 0.8539 | |
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| 0.3891 | 6.0 | 606 | nan | 0.6857 | 0.7020 | 0.6938 | 0.8563 | |
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| 0.3891 | 7.0 | 707 | nan | 0.6900 | 0.6673 | 0.6784 | 0.8580 | |
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| 0.3891 | 8.0 | 808 | nan | 0.6795 | 0.6782 | 0.6789 | 0.8514 | |
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| 0.3891 | 9.0 | 909 | nan | 0.6906 | 0.6691 | 0.6797 | 0.8571 | |
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| 0.1315 | 10.0 | 1010 | nan | 0.6816 | 0.6691 | 0.6753 | 0.8547 | |
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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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