---
base_model: UBC-NLP/MARBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: marbert-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. -->

# marbert-fully-supervised-arabic-propaganda

This model is a fine-tuned version of [UBC-NLP/MARBERT](https://huggingface.co/UBC-NLP/MARBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0833
- Accuracy: 0.9310
- Precision: 0.65
- Recall: 0.6341
- F1: 0.6420

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0618        | 1.0   | 40   | 0.7104          | 0.9429   | 0.8696    | 0.4878 | 0.625  |
| 0.0232        | 2.0   | 80   | 0.6505          | 0.9357   | 0.675     | 0.6585 | 0.6667 |
| 0.1792        | 3.0   | 120  | 0.9647          | 0.9357   | 0.6842    | 0.6341 | 0.6582 |
| 0.0015        | 4.0   | 160  | 1.1154          | 0.9381   | 0.7027    | 0.6341 | 0.6667 |
| 0.0017        | 5.0   | 200  | 1.0833          | 0.9310   | 0.65      | 0.6341 | 0.6420 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.13.3