Downloads · 30 days
3
7% of all-time downloads
visobert-finetuned-emotion
NPThanhh/visobert-finetuned-emotion
visobert-finetuned-emotion is a text classification model from NPThanhh. 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. --
All-time downloads
43
Public
Parameters
97.6M
781 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors390 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Feb 25, 2026
- Updated
- Feb 25, 2026
- SHA
- 92b3feb0
Try a prompt
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. -->
visobert-finetuned-emotion
This model is a fine-tuned version of uitnlp/visobert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8223
- Accuracy: 0.8774
- F1: 0.8738
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9725 | 1.0 | 179 | 0.7284 | 0.8724 | 0.8616 |
| 0.6232 | 2.0 | 358 | 0.7158 | 0.8756 | 0.8696 |
| 0.4918 | 3.0 | 537 | 0.7231 | 0.8819 | 0.8799 |
| 0.3846 | 4.0 | 716 | 0.8030 | 0.8756 | 0.8690 |
| 0.3125 | 5.0 | 895 | 0.8223 | 0.8774 | 0.8738 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Feb 25, 2026
- Updated
- Feb 25, 2026