---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: arabert-fully-supervised-arabic-propaganda
  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. -->

# arabert-fully-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: 0.4417
- Accuracy: 0.9167
- Precision: 0.5577
- Recall: 0.7073
- F1: 0.6237

## 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: 0.2
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5249        | 1.0   | 20   | 0.4933          | 0.7714   | 0.2901    | 0.9268 | 0.4419 |
| 0.303         | 2.0   | 40   | 0.3490          | 0.8571   | 0.3933    | 0.8537 | 0.5385 |
| 0.1552        | 3.0   | 60   | 0.3830          | 0.9048   | 0.5085    | 0.7317 | 0.6    |
| 0.1411        | 4.0   | 80   | 0.4215          | 0.9143   | 0.5455    | 0.7317 | 0.6250 |
| 0.1359        | 5.0   | 100  | 0.4417          | 0.9167   | 0.5577    | 0.7073 | 0.6237 |


### Framework versions

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