SourceData_GP-CHEM-ROLES_v_1-0-0_BioLinkBERT_large
This model is a fine-tuned version of michiyasunaga/BioLinkBERT-base on the source_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.0100
- Accuracy Score: 0.9975
- Precision: 0.9573
- Recall: 0.9649
- F1: 0.9611
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.0068 | 1.0 | 863 | 0.0100 | 0.9975 | 0.9573 | 0.9649 | 0.9611 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 2.10.1
- Tokenizers 0.12.1
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Evaluation results
- Precision on source_dataself-reported0.957
- Recall on source_dataself-reported0.965
- F1 on source_dataself-reported0.961