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merged the datasets (original + New)

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README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: aubmindlab/bert-base-arabertv02
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+ tags:
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+ - base_model:adapter:aubmindlab/bert-base-arabertv02
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+ - lora
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+ - transformers
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: saudi-eou-bert-classifier
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # saudi-eou-bert-classifier
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+
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+ This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3407
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+ - Accuracy: 0.864
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+ - Auc: 0.921
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
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+ | 0.712 | 1.0 | 295 | 0.6541 | 0.619 | 0.685 |
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+ | 0.5634 | 2.0 | 590 | 0.4838 | 0.781 | 0.845 |
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+ | 0.4258 | 3.0 | 885 | 0.4189 | 0.819 | 0.883 |
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+ | 0.3619 | 4.0 | 1180 | 0.3920 | 0.837 | 0.897 |
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+ | 0.3366 | 5.0 | 1475 | 0.3684 | 0.853 | 0.907 |
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+ | 0.3309 | 6.0 | 1770 | 0.3650 | 0.854 | 0.912 |
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+ | 0.3191 | 7.0 | 2065 | 0.3555 | 0.856 | 0.916 |
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+ | 0.3028 | 8.0 | 2360 | 0.3432 | 0.864 | 0.919 |
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+ | 0.3018 | 9.0 | 2655 | 0.3437 | 0.859 | 0.92 |
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+ | 0.2987 | 10.0 | 2950 | 0.3407 | 0.864 | 0.921 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.18.0
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+ - Transformers 4.57.3
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+ - Pytorch 2.9.0+cu126
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+ - Datasets 4.4.1
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+ - Tokenizers 0.22.1
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