---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: arabert-weakly-supervised-arabic-propaganda
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert-weakly-supervised-arabic-propaganda

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3223
- Accuracy: 0.8389
- Precision: 0.7865
- Recall: 0.7764
- F1: 0.7814

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3758        | 1.0   | 2272  | 0.3615          | 0.8193   | 0.7950    | 0.6909 | 0.7393 |
| 0.3421        | 2.0   | 4544  | 0.3431          | 0.8285   | 0.7523    | 0.8016 | 0.7762 |
| 0.3447        | 3.0   | 6816  | 0.3389          | 0.8305   | 0.7933    | 0.7345 | 0.7628 |
| 0.3229        | 4.0   | 9088  | 0.3297          | 0.8352   | 0.7725    | 0.7877 | 0.7800 |
| 0.3176        | 5.0   | 11360 | 0.3223          | 0.8389   | 0.7865    | 0.7764 | 0.7814 |


### Framework versions

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