metadata
library_name: transformers
license: mit
base_model: xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: CS221-xlnet-large-cased-finetuned-semeval-NT
results: []
CS221-xlnet-large-cased-finetuned-semeval-NT
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: 0.5455
- F1: 0.7320
- Roc Auc: 0.7940
- Accuracy: 0.4783
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|
| 0.4898 | 1.0 | 277 | 0.4345 | 0.4886 | 0.6537 | 0.3213 |
| 0.3807 | 2.0 | 554 | 0.3681 | 0.6681 | 0.7551 | 0.4296 |
| 0.265 | 3.0 | 831 | 0.3890 | 0.6765 | 0.7615 | 0.4693 |
| 0.1741 | 4.0 | 1108 | 0.4131 | 0.7120 | 0.7878 | 0.4404 |
| 0.0835 | 5.0 | 1385 | 0.4718 | 0.7303 | 0.7978 | 0.4765 |
| 0.0798 | 6.0 | 1662 | 0.5455 | 0.7320 | 0.7940 | 0.4783 |
| 0.0533 | 7.0 | 1939 | 0.6251 | 0.6976 | 0.7679 | 0.4386 |
| 0.032 | 8.0 | 2216 | 0.6953 | 0.7158 | 0.7885 | 0.4549 |
| 0.0179 | 9.0 | 2493 | 0.7133 | 0.7313 | 0.7984 | 0.4513 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0