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visobert-topic-neu-esc
bie-nhd/visobert-topic-neu-esc
visobert-topic-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
- b6dc0dbf
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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-topic_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: 0.6628
- Accuracy: 0.7970
- F1 Macro: 0.6432
- F1 Weighted: 0.7908
- Precision: 0.7001
- Recall: 0.6108
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 Macro | F1 Weighted | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| 0.7588 | 1.0 | 721 | 0.6692 | 0.7797 | 0.5853 | 0.7647 | 0.7122 | 0.5358 |
| 0.5034 | 2.0 | 1442 | 0.6628 | 0.7970 | 0.6432 | 0.7908 | 0.7001 | 0.6108 |
| 0.3576 | 3.0 | 2163 | 0.7099 | 0.7958 | 0.6507 | 0.7899 | 0.6997 | 0.6226 |
| 0.1779 | 4.0 | 2884 | 0.8471 | 0.7900 | 0.6470 | 0.7845 | 0.6975 | 0.6137 |
| 0.1101 | 5.0 | 3605 | 0.9037 | 0.7879 | 0.6586 | 0.7862 | 0.6777 | 0.6426 |
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