nllb-3.3B-myan-fine-tuned

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This model is a fine-tuned version of facebook/nllb-200-3.3B on a custom Burmese-English language dataset.

Model Details

Model Description

This model addresses the low-resource language gap for Burmese–English translation by fine-tuning NLLB-3.3B on a custom Burmese–English parallel dataset.

Base model: facebook/nllb-200-3.3B Fine-tuned for: Burmese → English Domain: general License:

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• Developed by: [LohithReddy]
• Model type: [Sequence-to-sequence Transformer (encoder-decoder) for machine translation]
• Language(s) (NLP): [Burmese (myan) , English (eng)]
• License: [More Information Needed]
• Finetuned from model: [facebook/nllb-200-3.3B]

Model Sources [optional]

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Uses

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Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

Hyperparameters

Learning rate: <value> Batch size: <value> Epochs: <value> Optimizer: <e.g. AdamW> Precision: <e.g. fp16 / bf16> Hardware: <e.g. 4x A100 80GB> Training time: <e.g. ~12 hours>

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Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

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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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Software

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Citation [optional]

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Glossary [optional]

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Framework versions

• PEFT 0.13.2