metadata
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: biobert
results: []
biobert
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: 0.4906
- Accuracy: 0.9444
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 791 | 0.2279 | 0.9384 |
| 0.1997 | 2.0 | 1582 | 0.3086 | 0.9326 |
| 0.0772 | 3.0 | 2373 | 0.3142 | 0.9305 |
| 0.0504 | 4.0 | 3164 | 0.3149 | 0.9417 |
| 0.0504 | 5.0 | 3955 | 0.3344 | 0.9414 |
| 0.0367 | 6.0 | 4746 | 0.3333 | 0.9430 |
| 0.0245 | 7.0 | 5537 | 0.3671 | 0.9409 |
| 0.0204 | 8.0 | 6328 | 0.4249 | 0.9395 |
| 0.0134 | 9.0 | 7119 | 0.3557 | 0.9456 |
| 0.0134 | 10.0 | 7910 | 0.4586 | 0.9384 |
| 0.0109 | 11.0 | 8701 | 0.5423 | 0.9374 |
| 0.0087 | 12.0 | 9492 | 0.4680 | 0.9458 |
| 0.0052 | 13.0 | 10283 | 0.4594 | 0.9458 |
| 0.0071 | 14.0 | 11074 | 0.5178 | 0.9389 |
| 0.0071 | 15.0 | 11865 | 0.4706 | 0.9421 |
| 0.0056 | 16.0 | 12656 | 0.4917 | 0.9435 |
| 0.0034 | 17.0 | 13447 | 0.4678 | 0.9447 |
| 0.0026 | 18.0 | 14238 | 0.4793 | 0.9447 |
| 0.0023 | 19.0 | 15029 | 0.4869 | 0.9458 |
| 0.0023 | 20.0 | 15820 | 0.4906 | 0.9444 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2