| | --- |
| | license: apache-2.0 |
| | base_model: michiyasunaga/BioLinkBERT-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - sem_eval_2024_task_2 |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: run1 |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: sem_eval_2024_task_2 |
| | type: sem_eval_2024_task_2 |
| | config: sem_eval_2024_task_2_source |
| | split: validation |
| | args: sem_eval_2024_task_2_source |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.64 |
| | - name: Precision |
| | type: precision |
| | value: 0.6582994120307553 |
| | - name: Recall |
| | type: recall |
| | value: 0.64 |
| | - name: F1 |
| | type: f1 |
| | value: 0.6292863762743282 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # run1 |
| |
|
| | This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the sem_eval_2024_task_2 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2153 |
| | - Accuracy: 0.64 |
| | - Precision: 0.6583 |
| | - Recall: 0.64 |
| | - F1: 0.6293 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | No log | 0.99 | 53 | 0.6971 | 0.515 | 0.5272 | 0.515 | 0.4537 | |
| | | 0.7029 | 2.0 | 107 | 0.6899 | 0.535 | 0.5413 | 0.535 | 0.5166 | |
| | | 0.7029 | 2.99 | 160 | 0.6855 | 0.535 | 0.5399 | 0.5350 | 0.5203 | |
| | | 0.6955 | 4.0 | 214 | 0.6698 | 0.565 | 0.5686 | 0.5650 | 0.5592 | |
| | | 0.6955 | 4.99 | 267 | 0.6722 | 0.57 | 0.5703 | 0.5700 | 0.5696 | |
| | | 0.6581 | 6.0 | 321 | 0.6367 | 0.61 | 0.6104 | 0.61 | 0.6096 | |
| | | 0.6581 | 6.99 | 374 | 0.6973 | 0.58 | 0.5905 | 0.58 | 0.5675 | |
| | | 0.5796 | 8.0 | 428 | 0.6925 | 0.625 | 0.6348 | 0.625 | 0.6180 | |
| | | 0.5796 | 8.99 | 481 | 0.7539 | 0.61 | 0.6364 | 0.61 | 0.5902 | |
| | | 0.4636 | 10.0 | 535 | 0.9313 | 0.575 | 0.6043 | 0.575 | 0.5429 | |
| | | 0.4636 | 10.99 | 588 | 0.9028 | 0.615 | 0.6227 | 0.615 | 0.6089 | |
| | | 0.3577 | 12.0 | 642 | 0.8694 | 0.615 | 0.6227 | 0.615 | 0.6089 | |
| | | 0.3577 | 12.99 | 695 | 0.9201 | 0.635 | 0.6494 | 0.635 | 0.6260 | |
| | | 0.3041 | 14.0 | 749 | 0.9186 | 0.645 | 0.6583 | 0.645 | 0.6374 | |
| | | 0.3041 | 14.99 | 802 | 1.1683 | 0.63 | 0.6578 | 0.63 | 0.6129 | |
| | | 0.2344 | 16.0 | 856 | 1.1405 | 0.625 | 0.6383 | 0.625 | 0.6158 | |
| | | 0.2344 | 16.99 | 909 | 1.2451 | 0.625 | 0.6474 | 0.625 | 0.6102 | |
| | | 0.208 | 18.0 | 963 | 1.1640 | 0.65 | 0.6671 | 0.65 | 0.6408 | |
| | | 0.208 | 18.99 | 1016 | 1.2081 | 0.64 | 0.6583 | 0.64 | 0.6293 | |
| | | 0.1757 | 19.81 | 1060 | 1.2153 | 0.64 | 0.6583 | 0.64 | 0.6293 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.0 |
| | |
