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# hadith-finetuned-ner3

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: 0.1498
- Precision: 0.8960
- Recall: 0.9633
- F1: 0.9284
- Accuracy: 0.9487

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4348        | 1.0   | 468  | 0.4253          | 0.7616    | 0.8286 | 0.7936 | 0.8541   |
| 0.3218        | 2.0   | 937  | 0.2721          | 0.8330    | 0.9113 | 0.8704 | 0.9095   |
| 0.375         | 3.0   | 1405 | 0.2008          | 0.8685    | 0.9423 | 0.9039 | 0.9316   |
| 0.1527        | 4.0   | 1874 | 0.1727          | 0.8791    | 0.9611 | 0.9183 | 0.9407   |
| 0.123         | 4.99  | 2340 | 0.1498          | 0.8960    | 0.9633 | 0.9284 | 0.9487   |


### 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-ner3", "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