---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fold_4
  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. -->

# fold_4

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4181
- Accuracy: 0.8452
- Macro F1: 0.8447
- Weighted F1: 0.8452
- F1 Pro: 0.8421
- F1 Against: 0.8571
- F1 Neutral: 0.8350

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
| 0.8777        | 1.1628 | 50   | 0.5462          | 0.8095   | 0.8101   | 0.8102      | 0.8468 | 0.7874     | 0.7959     |
| 0.4709        | 2.3256 | 100  | 0.4626          | 0.8274   | 0.8277   | 0.8275      | 0.8571 | 0.8034     | 0.8224     |
| 0.27          | 3.4884 | 150  | 0.4181          | 0.8452   | 0.8447   | 0.8452      | 0.8421 | 0.8571     | 0.8350     |
| 0.2101        | 4.6512 | 200  | 0.5017          | 0.8095   | 0.8088   | 0.8094      | 0.8421 | 0.8        | 0.7843     |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2