---
library_name: transformers
base_model: CausalNLP/gpt2-hf_multilingual-20
tags:
- generated_from_trainer
model-index:
- name: gpt2-multilingual-20-zh-repair_3epochs_lr1e-4
  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. -->

# gpt2-multilingual-20-zh-repair_3epochs_lr1e-4

This model is a fine-tuned version of [CausalNLP/gpt2-hf_multilingual-20](https://huggingface.co/CausalNLP/gpt2-hf_multilingual-20) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5282

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 3.6036        | 0.0626 | 500   | 3.6583          |
| 3.6222        | 0.1252 | 1000  | 3.6372          |
| 3.5958        | 0.1879 | 1500  | 3.6347          |
| 3.6297        | 0.2505 | 2000  | 3.6452          |
| 3.6016        | 0.3131 | 2500  | 3.6591          |
| 3.6284        | 0.3757 | 3000  | 3.6530          |
| 3.5823        | 0.4384 | 3500  | 3.6493          |
| 3.646         | 0.5010 | 4000  | 3.6412          |
| 3.6329        | 0.5636 | 4500  | 3.6358          |
| 3.5469        | 0.6262 | 5000  | 3.6302          |
| 3.5987        | 0.6889 | 5500  | 3.6242          |
| 3.4773        | 0.7515 | 6000  | 3.6181          |
| 3.561         | 0.8141 | 6500  | 3.6142          |
| 3.5243        | 0.8767 | 7000  | 3.6092          |
| 3.5998        | 0.9393 | 7500  | 3.6058          |
| 3.6267        | 1.0019 | 8000  | 3.6007          |
| 3.5314        | 1.0645 | 8500  | 3.5958          |
| 3.5579        | 1.1271 | 9000  | 3.5915          |
| 3.541         | 1.1897 | 9500  | 3.5861          |
| 3.5823        | 1.2524 | 10000 | 3.5820          |
| 3.534         | 1.3150 | 10500 | 3.5767          |
| 3.4906        | 1.3776 | 11000 | 3.5718          |
| 3.5538        | 1.4402 | 11500 | 3.5673          |
| 3.527         | 1.5029 | 12000 | 3.5631          |
| 3.5119        | 1.5655 | 12500 | 3.5584          |
| 3.4633        | 1.6281 | 13000 | 3.5537          |
| 3.5098        | 1.6907 | 13500 | 3.5503          |
| 3.4336        | 1.7534 | 14000 | 3.5474          |
| 3.5241        | 1.8160 | 14500 | 3.5444          |
| 3.4846        | 1.8786 | 15000 | 3.5409          |
| 3.4802        | 1.9412 | 15500 | 3.5385          |
| 3.5026        | 2.0038 | 16000 | 3.5368          |
| 3.494         | 2.0664 | 16500 | 3.5351          |
| 3.4524        | 2.1290 | 17000 | 3.5341          |
| 3.4478        | 2.1916 | 17500 | 3.5329          |
| 3.4458        | 2.2543 | 18000 | 3.5317          |
| 3.4925        | 2.3169 | 18500 | 3.5305          |
| 3.4913        | 2.3795 | 19000 | 3.5298          |
| 3.4331        | 2.4421 | 19500 | 3.5293          |
| 3.5182        | 2.5047 | 20000 | 3.5290          |
| 3.446         | 2.5674 | 20500 | 3.5286          |
| 3.5018        | 2.6300 | 21000 | 3.5285          |
| 3.475         | 2.6926 | 21500 | 3.5283          |
| 3.4299        | 2.7552 | 22000 | 3.5282          |
| 3.4538        | 2.8179 | 22500 | 3.5282          |
| 3.4471        | 2.8805 | 23000 | 3.5282          |
| 3.4295        | 2.9431 | 23500 | 3.5282          |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0
- Datasets 4.4.1
- Tokenizers 0.22.1