---
library_name: transformers
license: apache-2.0
base_model: CAMeL-Lab/bert-base-arabic-camelbert-mix
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: yaqeen_out
  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. -->

# yaqeen_out

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0117
- Accuracy: 1.0
- F1 Fake: 1.0
- F1 Real: 1.0
- F1 Macro: 1.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Fake | F1 Real | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:-------:|:--------:|
| No log        | 1.0   | 35   | 0.2376          | 0.9032   | 0.0     | 0.9492  | 0.4746   |
| 0.3653        | 2.0   | 70   | 0.0118          | 1.0      | 1.0     | 1.0     | 1.0      |
| 0.0202        | 3.0   | 105  | 0.0009          | 1.0      | 1.0     | 1.0     | 1.0      |
| 0.0202        | 4.0   | 140  | 0.0006          | 1.0      | 1.0     | 1.0     | 1.0      |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2