---
library_name: transformers
license: apache-2.0
base_model: CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camelbert-mix-sentiment-fold5
  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. -->

# camelbert-mix-sentiment-fold5

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0215
- Accuracy: 0.7917
- Macro F1: 0.7910
- Weighted F1: 0.7915
- F1 Pro: 0.8037
- F1 Against: 0.7939
- F1 Neutral: 0.7755

## 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: 2e-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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
| 0.7342        | 1.1628 | 50   | 0.6025          | 0.75     | 0.7486   | 0.7495      | 0.7818 | 0.7481     | 0.7158     |
| 0.3568        | 2.3256 | 100  | 0.7118          | 0.7560   | 0.7550   | 0.7554      | 0.7719 | 0.7538     | 0.7391     |
| 0.1872        | 3.4884 | 150  | 0.8953          | 0.7798   | 0.7797   | 0.7801      | 0.8    | 0.7761     | 0.7629     |
| 0.1084        | 4.6512 | 200  | 1.0203          | 0.7917   | 0.7910   | 0.7915      | 0.8037 | 0.7939     | 0.7755     |
| 0.0618        | 5.8140 | 250  | 1.1013          | 0.7798   | 0.7797   | 0.7800      | 0.7963 | 0.7752     | 0.7677     |
| 0.0460        | 6.9767 | 300  | 1.2741          | 0.7798   | 0.7793   | 0.7797      | 0.7963 | 0.7786     | 0.7629     |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2