---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: cs221-xlnet-base-cased-finetuned-20-epochs
  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-base-cased-finetuned-20-epochs

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6676
- F1: 0.7323
- Roc Auc: 0.8005
- Accuracy: 0.4422

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.0327        | 1.0   | 139  | 0.6538          | 0.7090 | 0.7827  | 0.4224   |
| 0.0168        | 2.0   | 278  | 0.6723          | 0.7309 | 0.8001  | 0.4206   |
| 0.0192        | 3.0   | 417  | 0.6676          | 0.7323 | 0.8005  | 0.4422   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.21.0