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tuning-sentiment-abp-v2.1
TungCan/tuning-sentiment-abp-v2.1
tuning-sentiment-abp-v2.1 is a text classification model from TungCan. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jul 2, 2025
- Updated
- Jul 2, 2025
- SHA
- 72d6452d
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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. -->
tuning-sentiment-abp-v2.1
This model is a fine-tuned version of 5CD-AI/Vietnamese-Sentiment-visobert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5126
- Accuracy: 0.7136
- F1: 0.5817
- Precision: 0.6377
- Recall: 0.6576
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: 32
- eval_batch_size: 64
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.5366 | 1.0 | 826 | 0.4949 | 0.7140 | 0.5837 | 0.6513 | 0.6571 |
| 0.4734 | 2.0 | 1652 | 0.4961 | 0.7146 | 0.5818 | 0.6756 | 0.6580 |
| 0.4645 | 3.0 | 2478 | 0.5126 | 0.7136 | 0.5817 | 0.6377 | 0.6576 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Jul 2, 2025
- Updated
- Jul 2, 2025