Aicha-zkr/M2M100-Algerian-Dialect-to-MSA

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Model Details

Model Description

This model is a fine-tuned version of the Facebook M2M100 (418M parameters), specifically adapted for translating Algerian dialect (ARQ) into Modern Standard Arabic (ARB). The fine-tuning process used a parallel dataset of 137,000 sentence pairs to improve the model’s translation accuracy for this specific language pair.

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Uses

Direct Use

This model can be used for: • Translating Algerian dialect (ARQ) text into Modern Standard Arabic (ARB). • Improving Arabic language understanding systems with a focus on Algerian dialect.

Downstream Use [optional]

This model could be used in language translation applications, chatbots, or other NLP systems that require Algerian dialect processing.

Out-of-Scope Use

•	It may not perform well with dialects other than Algerian or with highly ambiguous text.

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Bias, Risks, and Limitations

•	Bias: The model might reflect biases present in the training data, particularly linguistic or cultural biases.
•	Risks: Incorrect or misleading translations may occur, especially with highly ambiguous or slang terms.
•	Limitations: It is specific to Algerian dialect (ARQ) and Modern Standard Arabic (ARB) and may not generalize to other dialects, languages, or specialized domains.

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

The model was fine-tuned on a dataset of 137,000 sentence pairs containing Algerian dialect (ARQ) and Modern Standard Arabic (ARB). This parallel dataset allowed the model to specialize in translating this specific dialect.

Training Procedure

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Training Hyperparameters

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Evaluation

Testing Data, Factors & Metrics

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Results

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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