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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- bc2gm_corpus |
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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: biobert-base-cased-v1.2-bc2gm-ner |
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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: bc2gm_corpus |
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type: bc2gm_corpus |
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config: bc2gm_corpus |
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split: train |
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args: bc2gm_corpus |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7988356059445381 |
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- name: Recall |
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type: recall |
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value: 0.8243478260869566 |
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- name: F1 |
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type: f1 |
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value: 0.8113912231559292 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9772069842818806 |
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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-base-cased-v1.2-bc2gm-ner |
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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 bc2gm_corpus dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1528 |
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- Precision: 0.7988 |
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- Recall: 0.8243 |
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- F1: 0.8114 |
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- Accuracy: 0.9772 |
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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: 2e-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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| 0.057 | 1.0 | 782 | 0.0670 | 0.7446 | 0.8051 | 0.7736 | 0.9738 | |
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| 0.0586 | 2.0 | 1564 | 0.0689 | 0.7689 | 0.8106 | 0.7892 | 0.9755 | |
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| 0.0123 | 3.0 | 2346 | 0.0715 | 0.7846 | 0.8076 | 0.7959 | 0.9750 | |
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| 0.0002 | 4.0 | 3128 | 0.0896 | 0.7942 | 0.8199 | 0.8068 | 0.9767 | |
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| 0.0004 | 5.0 | 3910 | 0.1119 | 0.7971 | 0.8201 | 0.8084 | 0.9765 | |
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| 0.0004 | 6.0 | 4692 | 0.1192 | 0.7966 | 0.8337 | 0.8147 | 0.9768 | |
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| 0.013 | 7.0 | 5474 | 0.1274 | 0.7932 | 0.8266 | 0.8095 | 0.9773 | |
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| 0.0236 | 8.0 | 6256 | 0.1419 | 0.7976 | 0.8213 | 0.8093 | 0.9771 | |
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| 0.0004 | 9.0 | 7038 | 0.1519 | 0.8004 | 0.8261 | 0.8130 | 0.9772 | |
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| 0.0 | 10.0 | 7820 | 0.1528 | 0.7988 | 0.8243 | 0.8114 | 0.9772 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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