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---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert
  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. -->

# bert

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: 1.9191
- Macro F1: 0.3349
- Macro Precision: 0.3782
- Macro Recall: 0.3232
- Accuracy: 0.4557

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
| 1.8594        | 1.0   | 857  | 1.5842          | 0.2852   | 0.3360          | 0.2880       | 0.4542   |
| 1.3775        | 2.0   | 1714 | 1.5581          | 0.3394   | 0.3959          | 0.3210       | 0.4575   |
| 1.1436        | 3.0   | 2571 | 1.5983          | 0.3272   | 0.4183          | 0.3139       | 0.4631   |
| 0.9682        | 4.0   | 3428 | 1.7181          | 0.3383   | 0.3793          | 0.3254       | 0.4688   |
| 0.7683        | 5.0   | 4285 | 1.8410          | 0.3318   | 0.3755          | 0.3173       | 0.4535   |
| 0.6693        | 6.0   | 5142 | 1.9191          | 0.3349   | 0.3782          | 0.3232       | 0.4557   |


### Framework versions

- Transformers 4.53.0
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2