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# arabertv2-weakly-supervised-arabic-propaganda

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2702
- Accuracy: 0.8651
- Precision: 0.7667
- Recall: 0.6656
- F1: 0.7126

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2746        | 1.0   | 1648 | 0.2702          | 0.8651   | 0.7667    | 0.6656 | 0.7126 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "aubmindlab/bert-base-arabertv2", "model-index": [{"name": "arabertv2-weakly-supervised-arabic-propaganda", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:aubmindlab/bert-base-arabertv2 autotrain_compatible endpoints_compatible region:us