CS221-xlnet-large-cased-finetuned-semeval-aug
This model is a fine-tuned version of xlnet-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3323
- F1: 0.7655
- Roc Auc: 0.8218
- Accuracy: 0.5483
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 |
|---|---|---|---|---|---|---|
| 0.5847 | 1.0 | 277 | 0.5747 | 0.1535 | 0.5011 | 0.1409 |
| 0.5058 | 2.0 | 554 | 0.4907 | 0.3674 | 0.5986 | 0.2367 |
| 0.3991 | 3.0 | 831 | 0.4118 | 0.5551 | 0.6989 | 0.3921 |
| 0.3316 | 4.0 | 1108 | 0.3466 | 0.7102 | 0.7920 | 0.4770 |
| 0.2593 | 5.0 | 1385 | 0.3323 | 0.7655 | 0.8218 | 0.5483 |
| 0.1562 | 6.0 | 1662 | 0.3410 | 0.7838 | 0.8322 | 0.5962 |
| 0.1033 | 7.0 | 1939 | 0.3470 | 0.8023 | 0.8499 | 0.6134 |
| 0.0641 | 8.0 | 2216 | 0.3608 | 0.8102 | 0.8583 | 0.6314 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0