deberta-base-CoLA
This model is a fine-tuned version of microsoft/deberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1655
- Accuracy: 0.8482
- F1: 0.8961
- Roc Auc: 0.8987
- Mcc: 0.6288
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
Roc Auc |
Mcc |
| 0.5266 |
1.0 |
535 |
0.4138 |
0.8159 |
0.8698 |
0.8627 |
0.5576 |
| 0.3523 |
2.0 |
1070 |
0.3852 |
0.8387 |
0.8880 |
0.9041 |
0.6070 |
| 0.2479 |
3.0 |
1605 |
0.3981 |
0.8482 |
0.8901 |
0.9120 |
0.6447 |
| 0.1712 |
4.0 |
2140 |
0.4732 |
0.8558 |
0.9008 |
0.9160 |
0.6486 |
| 0.1354 |
5.0 |
2675 |
0.7181 |
0.8463 |
0.8938 |
0.9024 |
0.6250 |
| 0.0876 |
6.0 |
3210 |
0.8453 |
0.8520 |
0.8992 |
0.9123 |
0.6385 |
| 0.0682 |
7.0 |
3745 |
1.0282 |
0.8444 |
0.8938 |
0.9061 |
0.6189 |
| 0.0431 |
8.0 |
4280 |
1.1114 |
0.8463 |
0.8960 |
0.9010 |
0.6239 |
| 0.0323 |
9.0 |
4815 |
1.1663 |
0.8501 |
0.8970 |
0.8967 |
0.6340 |
| 0.0163 |
10.0 |
5350 |
1.1655 |
0.8482 |
0.8961 |
0.8987 |
0.6288 |
Framework versions
- Transformers 4.11.0
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
