---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-arabert-ned-latest
  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. -->

# fine-tuned-arabert-ned-latest

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: 0.1399
- Accuracy: 0.9741
- Precision: 0.9789
- Recall: 0.9818
- F1: 0.9803

## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1337        | 1.0   | 56232  | 0.1134          | 0.9716   | 0.9761    | 0.9809 | 0.9785 |
| 0.1031        | 2.0   | 112464 | 0.1135          | 0.9742   | 0.9765    | 0.9846 | 0.9805 |
| 0.0916        | 3.0   | 168696 | 0.1060          | 0.9745   | 0.9791    | 0.9822 | 0.9807 |
| 0.0812        | 4.0   | 224928 | 0.1138          | 0.9733   | 0.9787    | 0.9808 | 0.9798 |
| 0.076         | 5.0   | 281160 | 0.1277          | 0.9745   | 0.9782    | 0.9832 | 0.9807 |
| 0.0676        | 6.0   | 337392 | 0.1399          | 0.9741   | 0.9789    | 0.9818 | 0.9803 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1