metadata
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ddi_42
results: []
ddi_42
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: 0.2816
- Accuracy: 0.9535
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 791 | 0.1755 | 0.9411 |
| 0.2029 | 2.0 | 1582 | 0.1931 | 0.9495 |
| 0.0749 | 3.0 | 2373 | 0.2716 | 0.9475 |
| 0.0442 | 4.0 | 3164 | 0.2566 | 0.9515 |
| 0.0442 | 5.0 | 3955 | 0.2816 | 0.9535 |
| 0.0249 | 6.0 | 4746 | 0.3136 | 0.9471 |
| 0.0135 | 7.0 | 5537 | 0.3219 | 0.9475 |
| 0.0102 | 8.0 | 6328 | 0.3054 | 0.9503 |
| 0.006 | 9.0 | 7119 | 0.3304 | 0.9515 |
| 0.006 | 10.0 | 7910 | 0.3346 | 0.9507 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2