| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: michiyasunaga/BioLinkBERT-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - source_data |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: SourceData_GeneprodRoles_v1_0_0_BioLinkBERT_base |
| | results: |
| | - task: |
| | name: Token Classification |
| | type: token-classification |
| | dataset: |
| | name: source_data |
| | type: source_data |
| | config: ROLES_GP |
| | split: validation |
| | args: ROLES_GP |
| | metrics: |
| | - name: Precision |
| | type: precision |
| | value: 0.9220255327226995 |
| | - name: Recall |
| | type: recall |
| | value: 0.9266873360362509 |
| | - name: F1 |
| | type: f1 |
| | value: 0.9243505566657151 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # SourceData_GeneprodRoles_v1_0_0_BioLinkBERT_base |
| |
|
| | This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the source_data dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0137 |
| | - Accuracy Score: 0.9948 |
| | - Precision: 0.9220 |
| | - Recall: 0.9267 |
| | - F1: 0.9244 |
| | |
| | ## 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: 0.0001 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 128 |
| | - seed: 42 |
| | - optimizer: Use adafactor and the args are: |
| | No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 1.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:| |
| | | 0.0146 | 1.0 | 864 | 0.0137 | 0.9948 | 0.9220 | 0.9267 | 0.9244 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 1.13.1+cu117 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
