| --- |
| license: apache-2.0 |
| base_model: Mohamedd123321/Arabizi_Checkpoints-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: Arabizi_Checkpoints_vlast_d5 |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # Arabizi_Checkpoints_vlast_d5 |
| |
| This model is a fine-tuned version of [Mohamedd123321/Arabizi_Checkpoints-large](https://huggingface.co/Mohamedd123321/Arabizi_Checkpoints-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7717 |
| - Accuracy: 0.8692 |
| - F1: 0.8708 |
| - Precision: 0.8747 |
| - Recall: 0.8692 |
| |
| ## 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: 8 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.06 |
| - num_epochs: 6 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall | |
| |:-------------:|:------:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:| |
| | 0.4211 | 0.6906 | 2000 | 0.8541 | 0.8589 | 0.3843 | 0.8695 | 0.8541 | |
| | 0.3387 | 1.3812 | 4000 | 0.8618 | 0.8650 | 0.4193 | 0.8725 | 0.8618 | |
| | 0.2823 | 2.0718 | 6000 | 0.8621 | 0.8657 | 0.4879 | 0.8750 | 0.8621 | |
| | 0.2742 | 2.7624 | 8000 | 0.8609 | 0.8648 | 0.4871 | 0.8742 | 0.8609 | |
| | 0.2181 | 3.4530 | 10000 | 0.8650 | 0.8672 | 0.6036 | 0.8739 | 0.8650 | |
| | 0.1666 | 4.1436 | 12000 | 0.8689 | 0.8717 | 0.6616 | 0.8780 | 0.8689 | |
| | 0.1701 | 4.8343 | 14000 | 0.7497 | 0.8713 | 0.8727 | 0.8752 | 0.8713 | |
| | 0.1382 | 5.5249 | 16000 | 0.7717 | 0.8692 | 0.8708 | 0.8747 | 0.8692 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.2 |
| - Pytorch 2.8.0+cu129 |
| - Datasets 5.0.0 |
| - Tokenizers 0.19.1 |
| |
