---
library_name: transformers
license: mit
base_model: xlnet/xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: cs221-xlnet-large-cased-eng-finetuned-20-epochs-tapt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# cs221-xlnet-large-cased-eng-finetuned-20-epochs-tapt

This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5355
- F1: 0.7594
- Roc Auc: 0.8228
- Accuracy: 0.4506

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6009        | 1.0   | 73   | 0.5947          | 0.436  | 0.6134  | 0.1369   |
| 0.5678        | 2.0   | 146  | 0.5712          | 0.4273 | 0.6124  | 0.1456   |
| 0.5116        | 3.0   | 219  | 0.4825          | 0.6053 | 0.7128  | 0.2877   |
| 0.4375        | 4.0   | 292  | 0.4319          | 0.6749 | 0.7600  | 0.3501   |
| 0.3723        | 5.0   | 365  | 0.3959          | 0.7178 | 0.7919  | 0.4073   |
| 0.2906        | 6.0   | 438  | 0.3896          | 0.7329 | 0.8001  | 0.4385   |
| 0.2457        | 7.0   | 511  | 0.4272          | 0.7291 | 0.8009  | 0.4125   |
| 0.2035        | 8.0   | 584  | 0.4255          | 0.7516 | 0.8198  | 0.4385   |
| 0.1546        | 9.0   | 657  | 0.4514          | 0.7462 | 0.8126  | 0.4402   |
| 0.1238        | 10.0  | 730  | 0.4732          | 0.7518 | 0.8155  | 0.4419   |
| 0.0896        | 11.0  | 803  | 0.5441          | 0.7437 | 0.8104  | 0.4506   |
| 0.0659        | 12.0  | 876  | 0.5355          | 0.7594 | 0.8228  | 0.4506   |
| 0.0459        | 13.0  | 949  | 0.5450          | 0.7582 | 0.8200  | 0.4714   |
| 0.0436        | 14.0  | 1022 | 0.5919          | 0.7525 | 0.8164  | 0.4558   |
| 0.0366        | 15.0  | 1095 | 0.6016          | 0.7588 | 0.8226  | 0.4541   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0