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# DarijaBERT-finetuned-Arabic-SQuAD

This model is a fine-tuned version of [SI2M-Lab/DarijaBERT](https://huggingface.co/SI2M-Lab/DarijaBERT) on the [Mostafa3zazi/Arabic_SQuAD](https://huggingface.co/datasets/ZeyadAhmed/Arabic-SQuADv2.0) dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7451

## Model description

This model is a fine tuned version of DarijaBERT, specifically trained on the Arabic Squad dataset. It is designed to perform question answering in the Darija dialect, which is a colloquial Arabic variant spoken primarily in Morocco.

## Intended uses & limitations

- the fine-tuning was done on arabic dataset so the results may not always be accurate escpacially with rare word in darija



### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4



### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
{"tags": ["generated_from_trainer"], "datasets": ["Mostafa3zazi/Arabic_SQuAD"], "model-index": [{"name": "DarijaBERT-finetuned-Arabic-SQuAD", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer dataset:Mostafa3zazi/Arabic_SQuAD endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #dataset-Mostafa3zazi/Arabic_SQuAD #endpoints_compatible #region-us 




# DarijaBERT-finetuned-Arabic-SQuAD

This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the Mostafa3zazi/Arabic_SQuAD dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7451

## Model description

This model is a fine tuned version of DarijaBERT, specifically trained on the Arabic Squad dataset. It is designed to perform question answering in the Darija dialect, which is a colloquial Arabic variant spoken primarily in Morocco.

## Intended uses & limitations

- the fine-tuning was done on arabic dataset so the results may not always be accurate escpacially with rare word in darija



### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4



### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
# DarijaBERT-finetuned-Arabic-SQuAD

This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the Mostafa3zazi/Arabic_SQuAD dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7451 ## Model description

This model is a fine tuned version of DarijaBERT, specifically trained on the Arabic Squad dataset. It is designed to perform question answering in the Darija dialect, which is a colloquial Arabic variant spoken primarily in Morocco. ## Intended uses & limitations

- the fine-tuning was done on arabic dataset so the results may not always be accurate escpacially with rare word in darija ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4 ### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #dataset-Mostafa3zazi/Arabic_SQuAD #endpoints_compatible #region-us 
 # DarijaBERT-finetuned-Arabic-SQuAD

This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the Mostafa3zazi/Arabic_SQuAD dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7451 ## Model description

This model is a fine tuned version of DarijaBERT, specifically trained on the Arabic Squad dataset. It is designed to perform question answering in the Darija dialect, which is a colloquial Arabic variant spoken primarily in Morocco. ## Intended uses & limitations

- the fine-tuning was done on arabic dataset so the results may not always be accurate escpacially with rare word in darija ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4 ### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3