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--- |
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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: biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_ES |
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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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# biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_ES |
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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 CRAFT dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2251 |
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- Precision: 0.8276 |
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- Recall: 0.8411 |
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- F1: 0.8343 |
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- Accuracy: 0.9676 |
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## Model description |
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This model performs Named Entity Recognition for 6 entity tags: Sequence, Cell, Protein, Gene, Taxon, and Chemical from the CRAFT(Colorado Richly Annotated Full Text) Corpus in Spanish (MT translated) and English. Entity tags have been normalized and replaced from the original three letter code to a full name e.g. B-Protein, I-Chemical. |
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This model is trained on augmented data created using Entity Replacement. 20% of the entities were replaced using a list of entities for each entity tag obtained from the official ontologies for each entity class. Three datasets (original, augmented, MT translated CRAFT) were concatenated. |
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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: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 4 |
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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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| 0.0549 | 1.0 | 4078 | 0.1673 | 0.8056 | 0.8112 | 0.8084 | 0.9640 | |
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| 0.0233 | 2.0 | 8156 | 0.1733 | 0.8321 | 0.8244 | 0.8283 | 0.9662 | |
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| 0.0101 | 3.0 | 12234 | 0.1972 | 0.8336 | 0.8391 | 0.8363 | 0.9678 | |
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| 0.0036 | 4.0 | 16312 | 0.2251 | 0.8276 | 0.8411 | 0.8343 | 0.9676 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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