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# hadith-finetuned-ner2

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-msa-ner](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1591
- Precision: 0.8899
- Recall: 0.9602
- F1: 0.9237
- Accuracy: 0.9452

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5252        | 1.0   | 468  | 0.4358          | 0.7801    | 0.7819 | 0.7810 | 0.8478   |
| 0.228         | 2.0   | 937  | 0.2789          | 0.8225    | 0.9172 | 0.8673 | 0.9055   |
| 0.1561        | 3.0   | 1405 | 0.2077          | 0.8648    | 0.9395 | 0.9006 | 0.9301   |
| 0.1759        | 4.0   | 1874 | 0.1692          | 0.8914    | 0.9506 | 0.9201 | 0.9434   |
| 0.1496        | 4.99  | 2340 | 0.1591          | 0.8899    | 0.9602 | 0.9237 | 0.9452   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "CAMeL-Lab/bert-base-arabic-camelbert-msa-ner", "model-index": [{"name": "hadith-finetuned-ner2", "results": []}]}
transformers tensorboard safetensors bert token-classification generated_from_trainer base_model:CAMeL-Lab/bert-base-arabic-camelbert-msa-ner license:apache-2.0 autotrain_compatible endpoints_compatible region:us