| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| datasets: |
| - ncbi_disease |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: finetuned |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: ncbi_disease |
| type: ncbi_disease |
| config: ncbi_disease |
| split: validation |
| args: ncbi_disease |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.8246402877697842 |
| - name: Recall |
| type: recall |
| value: 0.8725023786869648 |
| - name: F1 |
| type: f1 |
| value: 0.8478964401294499 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9838910991496996 |
| --- |
| |
| <!-- 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. --> |
|
|
| # 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 ncbi_disease dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0568 |
| - Precision: 0.8246 |
| - Recall: 0.8725 |
| - F1: 0.8479 |
| - Accuracy: 0.9839 |
| |
| ## 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 | 170 | 0.0582 | 0.7621 | 0.8506 | 0.8040 | 0.9816 | |
| | No log | 2.0 | 340 | 0.0588 | 0.8074 | 0.8535 | 0.8298 | 0.9828 | |
| | 0.0712 | 3.0 | 510 | 0.0568 | 0.8246 | 0.8725 | 0.8479 | 0.9839 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.27.4 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.2 |
| |
