| --- |
| 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 |
| |
