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xlmr_norwegian_immigration2
AnonymousCS/xlmr_norwegian_immigration2
xlmr_norwegian_immigration2 is a text classification model from AnonymousCS. 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
- Aug 19, 2025
- Updated
- Aug 19, 2025
- SHA
- 1a3d7523
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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_norwegian_immigration2
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2207
- Accuracy: 0.9231
- 1-f1: 0.8810
- 1-recall: 0.8605
- 1-precision: 0.9024
- Balanced Acc: 0.9072
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.6746 | 1.0 | 5 | 0.6397 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.5485 | 2.0 | 10 | 0.6313 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6165 | 3.0 | 15 | 0.6220 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7306 | 4.0 | 20 | 0.6108 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.604 | 5.0 | 25 | 0.5968 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.5031 | 6.0 | 30 | 0.5714 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.5496 | 7.0 | 35 | 0.5302 | 0.6692 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.5351 | 8.0 | 40 | 0.4655 | 0.7769 | 0.4912 | 0.3256 | 1.0 | 0.6628 |
| 0.4308 | 9.0 | 45 | 0.3942 | 0.8538 | 0.7246 | 0.5814 | 0.9615 | 0.7850 |
| 0.3575 | 10.0 | 50 | 0.3077 | 0.9231 | 0.8780 | 0.8372 | 0.9231 | 0.9014 |
| 0.2808 | 11.0 | 55 | 0.2337 | 0.9308 | 0.8861 | 0.8140 | 0.9722 | 0.9012 |
| 0.2272 | 12.0 | 60 | 0.2053 | 0.9308 | 0.8889 | 0.8372 | 0.9474 | 0.9071 |
| 0.2462 | 13.0 | 65 | 0.2418 | 0.9 | 0.8539 | 0.8837 | 0.8261 | 0.8959 |
| 0.1188 | 14.0 | 70 | 0.2207 | 0.9231 | 0.8810 | 0.8605 | 0.9024 | 0.9072 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Aug 19, 2025
- Updated
- Aug 19, 2025