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# arabertv2-fully-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: 0.3894
- Accuracy: 0.9262
- Precision: 0.6042
- Recall: 0.7073
- F1: 0.6517

## 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: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4919        | 1.0   | 20   | 0.5087          | 0.8381   | 0.3516    | 0.7805 | 0.4848 |
| 0.3633        | 2.0   | 40   | 0.4010          | 0.8333   | 0.3474    | 0.8049 | 0.4853 |
| 0.2017        | 3.0   | 60   | 0.3635          | 0.9      | 0.4918    | 0.7317 | 0.5882 |
| 0.3071        | 4.0   | 80   | 0.3981          | 0.9333   | 0.6444    | 0.7073 | 0.6744 |
| 0.145         | 5.0   | 100  | 0.3894          | 0.9262   | 0.6042    | 0.7073 | 0.6517 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "aubmindlab/bert-base-arabertv2", "model-index": [{"name": "arabertv2-fully-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