---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_content
  results: []
---

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

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6934
- Macro F1: 0.5805
- Macro Precision: 0.5862
- Macro Recall: 0.5892
- Accuracy: 0.5991

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
| 1.2469        | 1.0   | 821  | 1.0233          | 0.5827   | 0.5896          | 0.5871       | 0.5991   |
| 0.8745        | 2.0   | 1642 | 1.0381          | 0.5912   | 0.6071          | 0.6001       | 0.6124   |
| 0.6973        | 3.0   | 2463 | 1.0917          | 0.5939   | 0.6149          | 0.6068       | 0.6191   |
| 0.4263        | 4.0   | 3284 | 1.3179          | 0.5801   | 0.5826          | 0.5951       | 0.6001   |
| 0.2791        | 5.0   | 4105 | 1.5275          | 0.5824   | 0.5921          | 0.5874       | 0.6019   |
| 0.2086        | 6.0   | 4926 | 1.6934          | 0.5805   | 0.5862          | 0.5892       | 0.5991   |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1