---
license: apache-2.0
base_model: hfl/chinese-xlnet-base
tags:
- generated_from_trainer
model-index:
- name: xlnet-base
  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. -->

# xlnet-base

This model is a fine-tuned version of [hfl/chinese-xlnet-base](https://huggingface.co/hfl/chinese-xlnet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.7194

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 8.1116        | 0.11  | 500  | 6.8678          |
| 6.8507        | 0.22  | 1000 | 6.7533          |
| 6.7394        | 0.34  | 1500 | 6.7035          |
| 6.6534        | 0.45  | 2000 | 6.6033          |
| 6.5451        | 0.56  | 2500 | 6.4870          |
| 6.4314        | 0.67  | 3000 | 6.3461          |
| 6.2783        | 0.78  | 3500 | 6.2090          |
| 6.1681        | 0.9   | 4000 | 6.0913          |
| 6.0757        | 1.01  | 4500 | 5.9937          |
| 5.9735        | 1.12  | 5000 | 5.9321          |
| 5.9025        | 1.23  | 5500 | 5.8552          |
| 5.8424        | 1.34  | 6000 | 5.8166          |
| 5.804         | 1.45  | 6500 | 5.7849          |
| 5.7535        | 1.57  | 7000 | 5.7420          |
| 5.7674        | 1.68  | 7500 | 5.7311          |
| 5.7613        | 1.79  | 8000 | 5.7269          |
| 5.7322        | 1.9   | 8500 | 5.7194          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0