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vit5-base-v2-paraphase_data
nguyen10001/vit5-base-v2-paraphase_data
vit5-base-v2-paraphase_data is a machine learning model from nguyen10001. 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 peft. 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
- peft
- License
- mit
- Access
- Public
- Created
- Oct 10, 2025
- Updated
- Oct 11, 2025
- SHA
- 02fdbbf5
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-base-v2-paraphase_data
This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1037
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3847 | 0.4980 | 3300 | 1.2644 |
| 1.2837 | 0.9961 | 6600 | 1.1851 |
| 1.23 | 1.4941 | 9900 | 1.1554 |
| 1.2291 | 1.9922 | 13200 | 1.1341 |
| 1.1839 | 2.4902 | 16500 | 1.1218 |
| 1.1908 | 2.9882 | 19800 | 1.1150 |
| 1.1778 | 3.4863 | 23100 | 1.1090 |
| 1.1674 | 3.9843 | 26400 | 1.1044 |
| 1.1712 | 4.4823 | 29700 | 1.1038 |
| 1.1709 | 4.9804 | 33000 | 1.1037 |
Framework versions
- PEFT 0.10.0
- Transformers 4.49.0
- Pytorch 2.4.1+cu118
- Datasets 4.1.1
- Tokenizers 0.21.0
- Library
- peft
- License
- mit
- Created
- Oct 10, 2025
- Updated
- Oct 11, 2025