---
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: 0.5455
- 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