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# hadith-finetuned-ner1

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: 0.1736
- Precision: 0.8899
- Recall: 0.9567
- F1: 0.9221
- Accuracy: 0.9441

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4895        | 1.0   | 468  | 0.4531          | 0.7392    | 0.8430 | 0.7877 | 0.8436   |
| 0.2379        | 2.0   | 937  | 0.2704          | 0.8371    | 0.9105 | 0.8723 | 0.9095   |
| 0.2792        | 3.0   | 1405 | 0.2122          | 0.8652    | 0.9429 | 0.9024 | 0.9302   |
| 0.1943        | 4.0   | 1874 | 0.1901          | 0.8769    | 0.9524 | 0.9131 | 0.9378   |
| 0.2443        | 4.99  | 2340 | 0.1736          | 0.8899    | 0.9567 | 0.9221 | 0.9441   |


### 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-ner1", "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