|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: danghuy1999/gpt2-viwiki |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: vietnamese-poem-gpt2-sauchu |
|
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. --> |
|
|
|
# vietnamese-poem-gpt2-sauchu |
|
|
|
This model is a fine-tuned version of [danghuy1999/gpt2-viwiki](https://huggingface.co/danghuy1999/gpt2-viwiki) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 5.9586 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 32 |
|
- 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: 12 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 1.0 | 17 | 7.5820 | |
|
| No log | 2.0 | 34 | 7.2608 | |
|
| No log | 3.0 | 51 | 6.9590 | |
|
| No log | 4.0 | 68 | 6.7325 | |
|
| No log | 5.0 | 85 | 6.5588 | |
|
| No log | 6.0 | 102 | 6.4239 | |
|
| No log | 7.0 | 119 | 6.3150 | |
|
| No log | 8.0 | 136 | 6.2274 | |
|
| No log | 9.0 | 153 | 6.1426 | |
|
| No log | 10.0 | 170 | 6.0750 | |
|
| No log | 11.0 | 187 | 6.0142 | |
|
| No log | 12.0 | 204 | 5.9586 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
