CS221-deberta-v3-base-finetuned-semeval-aug
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2787
- F1: 0.8148
- Roc Auc: 0.8588
- Accuracy: 0.6305
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.4659 | 1.0 | 277 | 0.4266 | 0.5416 | 0.6876 | 0.3595 |
| 0.3283 | 2.0 | 554 | 0.3517 | 0.7243 | 0.7902 | 0.4463 |
| 0.2599 | 3.0 | 831 | 0.3323 | 0.7266 | 0.8009 | 0.5104 |
| 0.1551 | 4.0 | 1108 | 0.2904 | 0.7961 | 0.8460 | 0.5863 |
| 0.1274 | 5.0 | 1385 | 0.2787 | 0.8148 | 0.8588 | 0.6305 |
| 0.0889 | 6.0 | 1662 | 0.2876 | 0.8213 | 0.8590 | 0.6531 |
| 0.0386 | 7.0 | 1939 | 0.2852 | 0.8443 | 0.8804 | 0.6829 |
| 0.0262 | 8.0 | 2216 | 0.2981 | 0.8550 | 0.8938 | 0.6911 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0