| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| datasets: |
| - biocreative_gene_mention |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: gene_finetuned |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: biocreative_gene_mention |
| type: biocreative_gene_mention |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.8389085168758926 |
| - name: Recall |
| type: recall |
| value: 0.8737864077669902 |
| - name: F1 |
| type: f1 |
| value: 0.8559923298178332 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9581707699896856 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # gene_finetuned |
| |
| This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the biocreative_gene_mention dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1217 |
| - Precision: 0.8389 |
| - Recall: 0.8738 |
| - F1: 0.8560 |
| - Accuracy: 0.9582 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 157 | 0.1379 | 0.7838 | 0.8403 | 0.8111 | 0.9487 | |
| | No log | 2.0 | 314 | 0.1188 | 0.8394 | 0.8642 | 0.8516 | 0.9570 | |
| | No log | 3.0 | 471 | 0.1217 | 0.8389 | 0.8738 | 0.8560 | 0.9582 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.27.4 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.2 |
| |
