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phobert-finetuned-viocd-v2
funa21/phobert-finetuned-viocd-v2
phobert-finetuned-viocd-v2 is a text classification model from funa21. Use it when you need a label for a piece of text. 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
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Aug 13, 2025
- Updated
- Aug 14, 2025
- SHA
- a6e3265e
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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. -->
phobert-finetuned-viocd-v2
This model is a fine-tuned version of vinai/phobert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3241
- Accuracy: 0.9307
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3494 | 1.0 | 138 | 0.2476 | 0.9179 |
| 0.1945 | 2.0 | 276 | 0.1765 | 0.9453 |
| 0.1307 | 3.0 | 414 | 0.2122 | 0.9361 |
| 0.065 | 4.0 | 552 | 0.2734 | 0.9361 |
| 0.0421 | 5.0 | 690 | 0.3241 | 0.9307 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Aug 13, 2025
- Updated
- Aug 14, 2025