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sd-ner-v2
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract on the source_data_nlp dataset. It achieves the following results on the evaluation set:
- Loss: 0.1551
- Accuracy Score: 0.9513
- Precision: 0.8030
- Recall: 0.8378
- F1: 0.8200
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: 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 |
---|---|---|---|---|---|---|---|
0.1082 | 1.0 | 785 | 0.1550 | 0.9493 | 0.7826 | 0.8402 | 0.8104 |
0.073 | 2.0 | 1570 | 0.1551 | 0.9513 | 0.8030 | 0.8378 | 0.8200 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 1.17.0
- Tokenizers 0.12.1