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ViT5_Restore_Diacritics_Vietnamese
qthuan2604/ViT5_Restore_Diacritics_Vietnamese
ViT5_Restore_Diacritics_Vietnamese is a machine learning model from qthuan2604. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- Nov 14, 2025
- Updated
- Nov 14, 2025
- SHA
- 21ec611c
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
ViT5_Restore_Diacritics_Vietnamese
This model is a fine-tuned version of VietAI/vit5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0897
- Model Preparation Time: 0.0058
- Cer: 0.2766
- Wer: 0.3313
- Char Acc: 0.6266
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: 12
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Cer | Wer | Char Acc |
|---|---|---|---|---|---|---|---|
| 5.3339 | 0.9985 | 333 | 0.3909 | 0.0058 | 0.5055 | 0.7208 | 0.2451 |
| 0.3762 | 2.0 | 667 | 0.2121 | 0.0058 | 0.3642 | 0.4929 | 0.4239 |
| 0.2409 | 2.9985 | 1000 | 0.1510 | 0.0058 | 0.3203 | 0.4134 | 0.5124 |
| 0.1789 | 4.0 | 1334 | 0.1212 | 0.0058 | 0.3018 | 0.3760 | 0.5581 |
| 0.1451 | 4.9985 | 1667 | 0.1054 | 0.0058 | 0.2890 | 0.3537 | 0.5900 |
| 0.1247 | 6.0 | 2001 | 0.0974 | 0.0058 | 0.2827 | 0.3434 | 0.6097 |
| 0.1137 | 6.9985 | 2334 | 0.0931 | 0.0058 | 0.2793 | 0.3369 | 0.6196 |
| 0.1064 | 8.0 | 2668 | 0.0906 | 0.0058 | 0.2774 | 0.3328 | 0.6244 |
| 0.103 | 8.9985 | 3001 | 0.0898 | 0.0058 | 0.2769 | 0.3317 | 0.6255 |
| 0.1016 | 9.9850 | 3330 | 0.0897 | 0.0058 | 0.2766 | 0.3313 | 0.6266 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1
- Type
- t5
- License
- mit
- Created
- Nov 14, 2025
- Updated
- Nov 14, 2025