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license: mit |
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datasets: |
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- opus_books |
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LlTRA stands for: Language to Language Transformer model from the paper "Attention is all you Need", building transformer model:Transformer model from scratch and using it for translation using pytorch. |
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Problem Statement: |
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In the rapidly evolving landscape of natural language processing (NLP) and machine translation, there exists a persistent challenge in achieving accurate and contextually rich language-to-language transformations. Existing models often struggle with capturing nuanced semantic meanings, context preservation, and maintaining grammatical coherence across different languages. Additionally, the demand for efficient cross-lingual communication and content generation has underscored the need for a versatile language transformer model that can seamlessly navigate the intricacies of diverse linguistic structures. |
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Goal: |
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Develop a specialized language-to-language transformer model that accurately translates from the Arabic language to the English language, ensuring semantic fidelity, contextual awareness, cross-lingual adaptability, and the retention of grammar and style. The model should provide efficient training and inference processes to make it practical and accessible for a wide range of applications, ultimately contributing to the advancement of Arabic-to-English language translation capabilities. |
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Dataset used: |
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from hugging Face huggingface/opus_infopankki |
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Configuration: |
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this is the settings of the model, You can customize the source and target languages, sequence lengths for each, the number of epochs, batch size, and more. |
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```python |
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def Get_configuration(): |
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return { |
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"batch_size": 8, |
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"num_epochs": 30, |
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"lr": 10**-4, |
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"sequence_length": 100, |
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"d_model": 512, |
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"datasource": 'opus_infopankki', |
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"source_language": "ar", |
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"target_language": "en", |
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"model_folder": "weights", |
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"model_basename": "tmodel_", |
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"preload": "latest", |
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"tokenizer_file": "tokenizer_{0}.json", |
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"experiment_name": "runs/tmodel" |
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} |
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``` |
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Training: |
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I used my drive to upload the project and then connected it to the Google Collab to train it: |
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- hours of training: 4 hours. |
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- epochs: 20. |
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- number of dataset rows: 2,934,399. |
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- size of the dataset: 95MB. |
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- size of the auto-converted parquet files: 153MB. |
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- Arabic tokens: 29999. |
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- English tokens: 15697. |
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- pre-trained model in collab. |
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- BLEU score from Arabic to English: 19.7 |
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