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hing_xlmr
amaan00z/hing_xlmr
hing_xlmr is a text classification model from amaan00z. 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
- Nov 5, 2025
- Updated
- Nov 5, 2025
- SHA
- a98bd8ff
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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. -->
hing_xlmr
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: 0.0339
- Accuracy: 0.993
- F1 Macro: 0.9930
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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.7382 | 1.0 | 844 | 0.0516 | 0.9877 | 0.9878 |
| 0.0395 | 2.0 | 1688 | 0.0562 | 0.99 | 0.9901 |
| 0.0261 | 3.0 | 2532 | 0.0284 | 0.994 | 0.9940 |
| 0.0128 | 4.0 | 3376 | 0.0339 | 0.993 | 0.9930 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Nov 5, 2025
- Updated
- Nov 5, 2025