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ViTay-combine-viet
FiveC/ViTay-combine-viet
ViTay-combine-viet is a machine learning model from FiveC. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- mbart
- Access
- Public
- Created
- Dec 30, 2025
- Updated
- Dec 30, 2025
- SHA
- f4d5c8de
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. -->
ViTay-combine-viet
This model is a fine-tuned version of FiveC/BartTay on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1796
- Sacrebleu: 14.0161
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: 16
- eval_batch_size: 16
- 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
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|---|---|---|---|---|
| 0.1265 | 1.0 | 5126 | 0.1818 | 10.7612 |
| 0.0813 | 2.0 | 10252 | 0.1721 | 13.3692 |
| 0.06 | 3.0 | 15378 | 0.1796 | 14.0161 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- transformers
- Type
- mbart
- License
- mit
- Created
- Dec 30, 2025
- Updated
- Dec 30, 2025