NLPGroupProject-Finetune-bio-mobilebert
This model is a fine-tuned version of nlpie/bio-mobilebert on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9925
- Accuracy: 0.737
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| No log |
0.25 |
250 |
0.8564 |
0.705 |
| 12.045 |
0.5 |
500 |
0.7663 |
0.726 |
| 12.045 |
0.75 |
750 |
0.7659 |
0.707 |
| 0.8388 |
1.0 |
1000 |
0.7144 |
0.737 |
| 0.8388 |
1.25 |
1250 |
0.7986 |
0.734 |
| 0.658 |
1.5 |
1500 |
0.8002 |
0.728 |
| 0.658 |
1.75 |
1750 |
0.7685 |
0.736 |
| 0.6945 |
2.0 |
2000 |
0.7751 |
0.738 |
| 0.6945 |
2.25 |
2250 |
1.2388 |
0.73 |
| 0.5058 |
2.5 |
2500 |
1.1562 |
0.733 |
| 0.5058 |
2.75 |
2750 |
0.9343 |
0.736 |
| 0.5251 |
3.0 |
3000 |
0.9925 |
0.737 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
