---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
base_model: aubmindlab/bert-base-arabertv02
model-index:
- name: AraBERT-finetuned-fnd
  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-finetuned-fnd

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5846
- Macro F1: 0.7751
- Accuracy: 0.7803
- Precision: 0.7740
- Recall: 0.7767

## 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: 16
- eval_batch_size: 16
- seed: 25
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| 0.5538        | 1.0   | 1597 | 0.5104          | 0.7183   | 0.7352   | 0.7323    | 0.7142 |
| 0.4689        | 2.0   | 3194 | 0.4849          | 0.7435   | 0.7574   | 0.7551    | 0.7392 |
| 0.3876        | 3.0   | 4791 | 0.4828          | 0.7693   | 0.7747   | 0.7682    | 0.7708 |
| 0.3152        | 4.0   | 6388 | 0.5412          | 0.7702   | 0.7747   | 0.7686    | 0.7729 |
| 0.2627        | 5.0   | 7985 | 0.5846          | 0.7751   | 0.7803   | 0.7740    | 0.7767 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1