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: 0.9958
- Precision: 0.6688
- Recall: 0.6721
- Accuracy: 0.6719
- F1: 0.6676
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 353 | 0.9151 | 0.5844 | 0.6236 | 0.6237 | 0.5781 |
| 0.9769 | 2.0 | 706 | 0.8475 | 0.6472 | 0.6592 | 0.6591 | 0.6506 |
| 0.6697 | 3.0 | 1059 | 0.8897 | 0.6657 | 0.6735 | 0.6740 | 0.6659 |
| 0.6697 | 4.0 | 1412 | 0.9515 | 0.6665 | 0.6769 | 0.6768 | 0.6690 |
| 0.463 | 5.0 | 1765 | 0.9958 | 0.6688 | 0.6721 | 0.6719 | 0.6676 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2