biobert-base-cased-v1.2-finetuned-ner
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.0706
- Precision: 0.8396
- Recall: 0.8731
- F1: 0.8561
- Accuracy: 0.9825
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 340 | 0.0691 | 0.8190 | 0.7868 | 0.8026 | 0.9777 |
0.101 | 2.0 | 680 | 0.0700 | 0.8334 | 0.8553 | 0.8442 | 0.9807 |
0.0244 | 3.0 | 1020 | 0.0706 | 0.8396 | 0.8731 | 0.8561 | 0.9825 |
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.3.0
- Tokenizers 0.12.1
- Downloads last month
- 7
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Dataset used to train hossay/biobert-base-cased-v1.2-finetuned-ner
Evaluation results
- Precision on ncbi_diseaseself-reported0.840
- Recall on ncbi_diseaseself-reported0.873
- F1 on ncbi_diseaseself-reported0.856
- Accuracy on ncbi_diseaseself-reported0.982