| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: bmd1905/vietnamese-correction-v2 |
| | tags: |
| | - text2text-generation |
| | - generated_from_trainer |
| | metrics: |
| | - sacrebleu |
| | model-index: |
| | - name: vietnamese-correction-finetuning |
| | 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-correction-finetuning |
| |
|
| | This model is a fine-tuned version of [bmd1905/vietnamese-correction-v2](https://huggingface.co/bmd1905/vietnamese-correction-v2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0479 |
| | - Sacrebleu: 98.4865 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - training_steps: 100000 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Sacrebleu | |
| | |:-------------:|:--------:|:------:|:---------------:|:---------:| |
| | | 0.0015 | 19.0840 | 5000 | 0.0479 | 98.4865 | |
| | | 0.0009 | 38.1679 | 10000 | 0.0527 | 98.4236 | |
| | | 0.0004 | 57.2519 | 15000 | 0.0565 | 98.4868 | |
| | | 0.0005 | 76.3359 | 20000 | 0.0592 | 98.4490 | |
| | | 0.0001 | 95.4198 | 25000 | 0.0635 | 98.4469 | |
| | | 0.0005 | 114.5038 | 30000 | 0.0618 | 98.4037 | |
| | | 0.0002 | 133.5878 | 35000 | 0.0683 | 98.2704 | |
| | | 0.0001 | 152.6718 | 40000 | 0.0692 | 98.3530 | |
| | | 0.0001 | 171.7557 | 45000 | 0.0645 | 98.4299 | |
| | | 0.0002 | 190.8397 | 50000 | 0.0706 | 98.3816 | |
| | | 0.0002 | 209.9237 | 55000 | 0.0683 | 98.3817 | |
| | | 0.0001 | 229.0076 | 60000 | 0.0692 | 98.4246 | |
| | | 0.0 | 248.0916 | 65000 | 0.0764 | 98.2300 | |
| | | 0.0001 | 267.1756 | 70000 | 0.0706 | 98.3508 | |
| | | 0.0 | 286.2595 | 75000 | 0.0711 | 98.3797 | |
| | | 0.0 | 305.3435 | 80000 | 0.0727 | 98.4148 | |
| | | 0.0 | 324.4275 | 85000 | 0.0744 | 98.3722 | |
| | | 0.0 | 343.5115 | 90000 | 0.0723 | 98.3660 | |
| | | 0.0 | 362.5954 | 95000 | 0.0760 | 98.3158 | |
| | | 0.0 | 381.6794 | 100000 | 0.0763 | 98.3326 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.0+cu128 |
| | - Datasets 4.4.2 |
| | - Tokenizers 0.22.2 |
| | |
