SourceData_NER_v_2-0-2_BioLinkBERT_base
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: 0.1314
- Accuracy Score: 0.9588
- Precision: 0.8313
- Recall: 0.8618
- F1: 0.8463
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: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 2.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.123 | 1.0 | 471 | 0.1366 | 0.9556 | 0.7986 | 0.8741 | 0.8346 |
0.085 | 2.0 | 942 | 0.1314 | 0.9588 | 0.8313 | 0.8618 | 0.8463 |
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-reported0.831
- Recall on source_dataself-reported0.862
- F1 on source_dataself-reported0.846