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vit5-vietnamese-summarization-gemini-synth-v2
AnTechAI/vit5-vietnamese-summarization-gemini-synth-v2
vit5-vietnamese-summarization-gemini-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 19, 2025
- Updated
- Nov 19, 2025
- SHA
- f7680766
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-gemini-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: 0.6605
- Rouge1: 0.7609
- Rouge2: 0.4649
- Rougel: 0.4828
- Rougelsum: 0.4825
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 |
|---|---|---|---|---|---|---|---|
| 0.9157 | 1.0 | 125 | 0.6635 | 0.7474 | 0.4533 | 0.4749 | 0.4749 |
| 0.8688 | 2.0 | 250 | 0.6600 | 0.7538 | 0.4599 | 0.4778 | 0.4776 |
| 0.786 | 3.0 | 375 | 0.6605 | 0.7609 | 0.4649 | 0.4828 | 0.4825 |
| 0.7689 | 4.0 | 500 | 0.6610 | 0.7619 | 0.4667 | 0.4827 | 0.4824 |
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 19, 2025
- Updated
- Nov 19, 2025