---
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