SourceData_GP-CHEM-ROLES_v_1-0-1_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: 0.0108
- Accuracy Score: 0.9973
- Precision: 0.9542
- Recall: 0.9630
- F1: 0.9586
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 |
---|---|---|---|---|---|---|---|
0.0073 | 1.0 | 863 | 0.0108 | 0.9973 | 0.9542 | 0.9630 | 0.9586 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 2.10.1
- Tokenizers 0.12.1
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Dataset used to train EMBO/SourceData_GP-CHEM-ROLES_v_1-0-1_BioLinkBERT_large
Evaluation results
- Precision on source_dataself-reported0.954
- Recall on source_dataself-reported0.963
- F1 on source_dataself-reported0.959