---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CS221-xlnet-large-cased-finetuned-semeval-NT

This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/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