---
base_model: uer/gpt2-chinese-cluecorpussmall
tags:
- generated_from_trainer
model-index:
- name: LCIA_Test3_gpt2_small
  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. -->

# LCIA_Test3_gpt2_small

This model is a fine-tuned version of [uer/gpt2-chinese-cluecorpussmall](https://huggingface.co/uer/gpt2-chinese-cluecorpussmall) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1054

## 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: 18
- eval_batch_size: 18
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 21   | 0.7690          |
| No log        | 2.0   | 42   | 0.6252          |
| No log        | 3.0   | 63   | 0.4116          |
| No log        | 4.0   | 84   | 0.1728          |
| No log        | 5.0   | 105  | 0.1211          |
| No log        | 6.0   | 126  | 0.1188          |
| No log        | 7.0   | 147  | 0.1166          |
| No log        | 8.0   | 168  | 0.1113          |
| No log        | 9.0   | 189  | 0.1090          |
| No log        | 10.0  | 210  | 0.1100          |
| No log        | 11.0  | 231  | 0.1029          |
| No log        | 12.0  | 252  | 0.1016          |
| No log        | 13.0  | 273  | 0.0963          |
| No log        | 14.0  | 294  | 0.0998          |
| No log        | 15.0  | 315  | 0.0935          |
| No log        | 16.0  | 336  | 0.0956          |
| No log        | 17.0  | 357  | 0.0925          |
| No log        | 18.0  | 378  | 0.0913          |
| No log        | 19.0  | 399  | 0.0993          |
| No log        | 20.0  | 420  | 0.0981          |
| No log        | 21.0  | 441  | 0.0946          |
| No log        | 22.0  | 462  | 0.1039          |
| No log        | 23.0  | 483  | 0.0984          |
| 0.1655        | 24.0  | 504  | 0.0977          |
| 0.1655        | 25.0  | 525  | 0.1018          |
| 0.1655        | 26.0  | 546  | 0.1040          |
| 0.1655        | 27.0  | 567  | 0.0988          |
| 0.1655        | 28.0  | 588  | 0.1047          |
| 0.1655        | 29.0  | 609  | 0.1059          |
| 0.1655        | 30.0  | 630  | 0.1061          |
| 0.1655        | 31.0  | 651  | 0.1064          |
| 0.1655        | 32.0  | 672  | 0.1049          |
| 0.1655        | 33.0  | 693  | 0.1038          |
| 0.1655        | 34.0  | 714  | 0.1054          |
| 0.1655        | 35.0  | 735  | 0.1016          |
| 0.1655        | 36.0  | 756  | 0.1076          |
| 0.1655        | 37.0  | 777  | 0.1047          |
| 0.1655        | 38.0  | 798  | 0.1055          |
| 0.1655        | 39.0  | 819  | 0.1056          |
| 0.1655        | 40.0  | 840  | 0.1054          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1