---
library_name: transformers
license: mit
base_model: xlnet/xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlnet_xlnet-large-cased
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xlnet_xlnet-large-cased

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: 1.4041
- Accuracy: 0.4479

## 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: 5e-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: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.419         | 1.0   | 283  | 1.4054          | 0.4479   |
| 1.4137        | 2.0   | 566  | 1.3887          | 0.4479   |
| 1.4122        | 3.0   | 849  | 1.3666          | 0.4479   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.4.0
- Tokenizers 0.21.1