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-corpus-ptc
results: []
biobert-v1.1-text-classifier-corpus-ptc
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: 0.8871
- Precision: 0.6734
- Recall: 0.6476
- Accuracy: 0.7495
- F1: 0.6556
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| 0.8749 | 1.0 | 801 | 0.7585 | 0.5507 | 0.5801 | 0.7291 | 0.5628 |
| 0.608 | 2.0 | 1602 | 0.7347 | 0.6817 | 0.5910 | 0.7407 | 0.5786 |
| 0.5071 | 3.0 | 2403 | 0.8002 | 0.6852 | 0.6272 | 0.7501 | 0.6331 |
| 0.3756 | 4.0 | 3204 | 0.8416 | 0.6989 | 0.6411 | 0.7529 | 0.6528 |
| 0.3092 | 5.0 | 4005 | 0.8871 | 0.6734 | 0.6476 | 0.7495 | 0.6556 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2