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

# shared-task_content_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: 1.6166
- Macro F1: 0.5238
- Macro Precision: 0.5506
- Macro Recall: 0.5088
- Accuracy: 0.5373

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
| 1.3557        | 1.0   | 857  | 1.1959          | 0.5085   | 0.5507          | 0.4906       | 0.5293   |
| 1.006         | 2.0   | 1714 | 1.1857          | 0.5130   | 0.5522          | 0.5042       | 0.5339   |
| 0.8063        | 3.0   | 2571 | 1.2605          | 0.5181   | 0.5385          | 0.5079       | 0.5321   |
| 0.6613        | 4.0   | 3428 | 1.3541          | 0.5206   | 0.5486          | 0.5064       | 0.5346   |
| 0.5106        | 5.0   | 4285 | 1.5204          | 0.5151   | 0.5460          | 0.4981       | 0.5304   |
| 0.4373        | 6.0   | 5142 | 1.6166          | 0.5238   | 0.5506          | 0.5088       | 0.5373   |


### Framework versions

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