---
library_name: transformers
license: mit
base_model: xlnet/xlnet-large-cased
tags:
- generated_from_trainer
model-index:
- name: cs221-xlnet-large-cased-finetuned
  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-finetuned

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: 0.5884
- Bce Loss: 0.5884

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bce Loss |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5902        | 1.0   | 139  | 0.5891          | 0.5891   |
| 0.5564        | 2.0   | 278  | 0.5912          | 0.5912   |
| 0.5744        | 3.0   | 417  | 0.5889          | 0.5889   |
| 0.5504        | 4.0   | 556  | 0.5884          | 0.5884   |


### Framework versions

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