---
library_name: transformers
base_model: NlpHUST/gpt2-vietnamese
tags:
- generated_from_trainer
model-index:
- name: vietnamese-poem-hustgpt2-namchu
  results: []
datasets:
- phamson02/vietnamese-poetry-corpus
---

<!-- 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. -->

# vietnamese-poem-hustgpt2-namchu

This model is a fine-tuned version of [NlpHUST/gpt2-vietnamese](https://huggingface.co/NlpHUST/gpt2-vietnamese) on [phamson02/vietnamese-poetry-corpus](https://huggingface.co/datasets/phamson02/vietnamese-poetry-corpus).
It achieves the following results on the evaluation set:
- Loss: 3.6570

## 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: 4
- eval_batch_size: 4
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.8677        | 1.0   | 2037  | 3.8531          |
| 3.7534        | 2.0   | 4074  | 3.7680          |
| 3.6882        | 3.0   | 6111  | 3.7256          |
| 3.6229        | 4.0   | 8148  | 3.7001          |
| 3.5661        | 5.0   | 10185 | 3.6829          |
| 3.5535        | 6.0   | 12222 | 3.6715          |
| 3.5146        | 7.0   | 14259 | 3.6635          |
| 3.505         | 8.0   | 16296 | 3.6602          |
| 3.4933        | 9.0   | 18333 | 3.6578          |
| 3.4628        | 10.0  | 20370 | 3.6570          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0