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xlmr_multilabel_websites_bertmultiling_uncased
rgusseinov/xlmr_multilabel_websites_bertmultiling_uncased
xlmr_multilabel_websites_bertmultiling_uncased 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Mar 3, 2026
- Updated
- Mar 3, 2026
- SHA
- c35aa786
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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_uncased
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4916
- Accuracy: 0.8230
- F1 Macro: 0.8173
- Precision Macro: 0.8153
- Recall Macro: 0.8243
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|
| 0.0002 | 1.0 | 33 | 1.4612 | 0.8319 | 0.8263 | 0.8235 | 0.8310 |
| 0.0001 | 2.0 | 66 | 1.4851 | 0.8230 | 0.8164 | 0.8140 | 0.8243 |
| 0.0001 | 3.0 | 99 | 1.4916 | 0.8230 | 0.8173 | 0.8153 | 0.8243 |
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
- bert
- License
- apache-2.0
- Created
- Mar 3, 2026
- Updated
- Mar 3, 2026