---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Twitter_concatenatewithPrompt-fold4
  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. -->

# Twitter_concatenatewithPrompt-fold4

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: 0.3991
- Accuracy: 0.8690
- Macro F1: 0.8675
- Weighted F1: 0.8688
- F1 Pro: 0.9123
- F1 Against: 0.8667
- F1 Neutral: 0.8235

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
| 0.9325        | 1.1628 | 50   | 0.5782          | 0.7857   | 0.7852   | 0.7850      | 0.8376 | 0.7414     | 0.7767     |
| 0.5357        | 2.3256 | 100  | 0.4209          | 0.8333   | 0.8332   | 0.8335      | 0.8571 | 0.8226     | 0.82       |
| 0.3501        | 3.4884 | 150  | 0.4185          | 0.8452   | 0.8439   | 0.8449      | 0.8929 | 0.8346     | 0.8041     |
| 0.2385        | 4.6512 | 200  | 0.3991          | 0.8690   | 0.8675   | 0.8688      | 0.9123 | 0.8667     | 0.8235     |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2