---
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-arabertv2_1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-arabertv2_1

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8943
- Accuracy: 0.65

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6125        | 4.57  | 1000 | 0.8943          | 0.65     |
| 0.1438        | 9.13  | 2000 | 1.4417          | 0.622    |
| 0.0537        | 13.7  | 3000 | 2.1144          | 0.62     |
| 0.0346        | 18.26 | 4000 | 2.5203          | 0.643    |
| 0.0013        | 22.83 | 5000 | 2.6799          | 0.636    |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1