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visobert-sentiment-neu-esc
bie-nhd/visobert-sentiment-neu-esc
visobert-sentiment-neu-esc is a text classification model from bie-nhd. 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
- Jan 27, 2026
- Updated
- Jan 27, 2026
- SHA
- 8753e5b5
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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. -->
visobert-sentiment-neu-esc
This model is a fine-tuned version of uitnlp/visobert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4683
- Accuracy: 0.8290
- F1 Weighted: 0.8250
- F1 Macro: 0.7526
- Precision: 0.8283
- Recall: 0.8290
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: 32
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | F1 Macro | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| 0.4471 | 1.0 | 721 | 0.4617 | 0.8209 | 0.8182 | 0.7380 | 0.8176 | 0.8209 |
| 0.3817 | 2.0 | 1442 | 0.4683 | 0.8290 | 0.8250 | 0.7526 | 0.8283 | 0.8290 |
| 0.2134 | 3.0 | 2163 | 0.5516 | 0.8278 | 0.8241 | 0.7526 | 0.8231 | 0.8278 |
| 0.1048 | 4.0 | 2884 | 0.8084 | 0.8230 | 0.8181 | 0.7453 | 0.8168 | 0.8230 |
| 0.0488 | 5.0 | 3605 | 0.8976 | 0.8188 | 0.8163 | 0.7437 | 0.8156 | 0.8188 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026