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AraModernBert-coherence-clean
yakz1/AraModernBert-coherence-clean
AraModernBert-coherence-clean is a text classification model from yakz1. 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
- modernbert
- Access
- Public
- Created
- Apr 25, 2026
- Updated
- Apr 26, 2026
- SHA
- 320a4131
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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. -->
AraModernBert-coherence-clean
This model is a fine-tuned version of NAMAA-Space/AraModernBert-Base-V1.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6959
- Accuracy: 0.8738
- Macro F1: 0.7566
- F1 Incoherent: 0.5877
- Precision Incoherent: 0.6381
- Recall Incoherent: 0.5447
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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | F1 Incoherent | Precision Incoherent | Recall Incoherent |
|---|---|---|---|---|---|---|---|---|
| 6.5997 | 1.0 | 375 | 0.3938 | 0.8362 | 0.5991 | 0.2907 | 0.5102 | 0.2033 |
| 4.6902 | 2.0 | 750 | 0.4099 | 0.8550 | 0.5997 | 0.2800 | 0.7778 | 0.1707 |
| 3.4927 | 3.0 | 1125 | 0.4294 | 0.8725 | 0.7313 | 0.5366 | 0.6707 | 0.4472 |
| 0.9152 | 4.0 | 1500 | 0.6959 | 0.8738 | 0.7566 | 0.5877 | 0.6381 | 0.5447 |
Framework versions
- Transformers 5.6.2
- Pytorch 2.4.1+cu124
- Datasets 4.8.4
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Apr 25, 2026
- Updated
- Apr 26, 2026