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: 0.6052
- F1: 0.7508
- Roc Auc: 0.8048
- Accuracy: 0.4946
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 |
|---|---|---|---|---|---|---|
| 0.5646 | 1.0 | 139 | 0.5839 | 0.1510 | 0.5 | 0.1516 |
| 0.423 | 2.0 | 278 | 0.4050 | 0.5543 | 0.6899 | 0.3809 |
| 0.3337 | 3.0 | 417 | 0.3495 | 0.7121 | 0.7705 | 0.4639 |
| 0.2423 | 4.0 | 556 | 0.3842 | 0.7301 | 0.8008 | 0.4801 |
| 0.168 | 5.0 | 695 | 0.4278 | 0.7409 | 0.8005 | 0.4639 |
| 0.0905 | 6.0 | 834 | 0.4894 | 0.7207 | 0.7868 | 0.4856 |
| 0.0619 | 7.0 | 973 | 0.5203 | 0.7238 | 0.7784 | 0.4422 |
| 0.0371 | 8.0 | 1112 | 0.5356 | 0.7507 | 0.8097 | 0.4747 |
| 0.0253 | 9.0 | 1251 | 0.6092 | 0.7405 | 0.7970 | 0.4783 |
| 0.0086 | 10.0 | 1390 | 0.6052 | 0.7508 | 0.8048 | 0.4946 |
| 0.0102 | 11.0 | 1529 | 0.6632 | 0.7381 | 0.7978 | 0.4639 |
| 0.0048 | 12.0 | 1668 | 0.6512 | 0.7483 | 0.8060 | 0.4874 |
| 0.0032 | 13.0 | 1807 | 0.6595 | 0.7399 | 0.7965 | 0.4819 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0