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vit5-vietnamese-summarization-gpt-synth-v2
AnTechAI/vit5-vietnamese-summarization-gpt-synth-v2
vit5-vietnamese-summarization-gpt-synth-v2 is a machine learning model from AnTechAI. 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
- t5
- Access
- Public
- Created
- Nov 20, 2025
- Updated
- Nov 20, 2025
- SHA
- 5b0c312e
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-vietnamese-summarization-gpt-synth-v2
This model is a fine-tuned version of antechit03/vit5-vietnamese-summarization-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6617
- Rouge1: 0.7639
- Rouge2: 0.4686
- Rougel: 0.4836
- Rougelsum: 0.4834
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.9127 | 1.0 | 250 | 0.6681 | 0.7532 | 0.4584 | 0.4766 | 0.4765 |
| 0.8177 | 2.0 | 500 | 0.6612 | 0.7577 | 0.4638 | 0.4801 | 0.4799 |
| 0.7898 | 3.0 | 750 | 0.6635 | 0.7624 | 0.4679 | 0.4809 | 0.4808 |
| 0.7595 | 4.0 | 1000 | 0.6617 | 0.7639 | 0.4686 | 0.4836 | 0.4834 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- Nov 20, 2025
- Updated
- Nov 20, 2025