---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-arabert-arabGloss-ds
  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-arabGloss-ds

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: 0.7052
- Accuracy: 0.8295
- Precision: 0.8016
- Recall: 0.6175
- F1: 0.6976

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4109        | 1.0   | 9494  | 0.4561          | 0.8065   | 0.6987    | 0.6900 | 0.6943 |
| 0.297         | 2.0   | 18988 | 0.4803          | 0.8213   | 0.7353    | 0.6855 | 0.7095 |
| 0.2316        | 3.0   | 28482 | 0.5530          | 0.8278   | 0.7438    | 0.7007 | 0.7216 |
| 0.1885        | 4.0   | 37976 | 0.7052          | 0.8295   | 0.8016    | 0.6175 | 0.6976 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1