metadata
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: biobert-v1.1-text-classifier
results: []
biobert-v1.1-text-classifier
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2669
- Precision: 0.9098
- Recall: 0.9091
- Accuracy: 0.9089
- F1: 0.9089
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 154 | 0.3413 | 0.8822 | 0.8813 | 0.8804 | 0.8808 |
| No log | 2.0 | 308 | 0.2918 | 0.8945 | 0.8836 | 0.8845 | 0.8848 |
| No log | 3.0 | 462 | 0.2669 | 0.9098 | 0.9091 | 0.9089 | 0.9089 |
| 0.3597 | 4.0 | 616 | 0.2781 | 0.9175 | 0.9174 | 0.9170 | 0.9170 |
| 0.3597 | 5.0 | 770 | 0.2797 | 0.9203 | 0.9206 | 0.9203 | 0.9204 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2