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xlmr_multilabel_websites_bertmultiling_cased
rgusseinov/xlmr_multilabel_websites_bertmultiling_cased
xlmr_multilabel_websites_bertmultiling_cased is a text classification model from rgusseinov. 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
- xlm-roberta
- Access
- Public
- Created
- Mar 3, 2026
- Updated
- Mar 25, 2026
- SHA
- 9a74d2f8
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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. -->
xlmr_multilabel_websites_bertmultiling_cased
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2813
- Accuracy: 0.9067
- F1 Macro: 0.9039
- Precision Macro: 0.9040
- Recall Macro: 0.9100
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: 8
- eval_batch_size: 16
- 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_steps: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|
| 1.0395 | 1.0 | 28 | 0.7680 | 0.7867 | 0.7401 | 0.8865 | 0.7202 |
| 0.5872 | 2.0 | 56 | 0.3103 | 0.8933 | 0.8937 | 0.9188 | 0.8791 |
| 0.3051 | 3.0 | 84 | 0.3119 | 0.8933 | 0.8949 | 0.9236 | 0.8791 |
| 0.1812 | 4.0 | 112 | 0.3469 | 0.88 | 0.8753 | 0.8694 | 0.8897 |
| 0.1546 | 5.0 | 140 | 0.2813 | 0.9067 | 0.9039 | 0.9040 | 0.9100 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Mar 3, 2026
- Updated
- Mar 25, 2026