bert-base-arabic-TunDC

This model is a fine-tuned version of asafaya/bert-base-arabic on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5931

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss
0.4712	1.0	1754	0.5598
0.3853	2.0	3508	0.5205
0.434	3.0	5262	0.5253
0.6624	4.0	7016	0.6354
0.374	5.0	8770	0.5931

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.1
• Tokenizers 0.21.0

Classification Report

Metric	Precision	Recall	F1-Score	Support
Class 0	0.81	0.83	0.82	3311
Class 1	0.78	0.77	0.78	2703
Accuracy			0.80	6014
Macro Avg	0.80	0.80	0.80	6014
Weighted Avg	0.80	0.80	0.80	6014

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