metadata
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: NHS-dmis-binary
results: []
NHS-dmis-binary
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4752
- Accuracy: 0.8158
- Precision: 0.8102
- Recall: 0.8064
- F1: 0.8081
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: 3e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0543 | 1.0 | 397 | 0.3985 | 0.8240 | 0.8232 | 0.8089 | 0.8141 |
| 0.1033 | 2.0 | 794 | 0.4902 | 0.7817 | 0.7913 | 0.7996 | 0.7811 |
| 2.162 | 3.0 | 1191 | 0.4752 | 0.8158 | 0.8102 | 0.8064 | 0.8081 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2