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answerdotai-ModernBERT-large-arabic-fp16-allagree
Qanadil/answerdotai-ModernBERT-large-arabic-fp16-allagree
answerdotai-ModernBERT-large-arabic-fp16-allagree is a text classification model from Qanadil. 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 13, 2025
- Updated
- Apr 13, 2025
- SHA
- 99de12e7
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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. -->
answerdotai-ModernBERT-large-arabic-fp16-allagree
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4373
- Accuracy: 0.8358
- Precision: 0.8350
- Recall: 0.8358
- F1: 0.8354
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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_ratio: 0.3
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.945 | 0.7463 | 50 | 0.6971 | 0.7127 | 0.7107 | 0.7127 | 0.7115 |
| 1.2749 | 1.4925 | 100 | 0.5650 | 0.7892 | 0.7928 | 0.7892 | 0.7898 |
| 1.1245 | 2.2388 | 150 | 0.6353 | 0.7491 | 0.8034 | 0.7491 | 0.7572 |
| 1.024 | 2.9851 | 200 | 0.4373 | 0.8358 | 0.8350 | 0.8358 | 0.8354 |
| 0.8063 | 3.7313 | 250 | 0.4471 | 0.8246 | 0.8413 | 0.8246 | 0.8294 |
| 0.6552 | 4.4776 | 300 | 0.4742 | 0.8293 | 0.8424 | 0.8293 | 0.8203 |
| 0.5445 | 5.2239 | 350 | 0.4599 | 0.8535 | 0.8552 | 0.8535 | 0.8515 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Apr 13, 2025
- Updated
- Apr 13, 2025