This repository contains a Transformer-based AI model fine-tuned for English to Spanish text translation. The model has been trained, quantized (FP16), and tested for quality and scoring. It delivers high-accuracy translations and is suitable for real-world use cases such as educational tools, real-time communication, and travel assistants.
1from datasets import load_dataset
2
3dataset = load_dataset("OscarNav/spa-eng", lang1="en", lang2="es")
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Pretrained Base Model: Helsinki-NLP/opus-mt-en-es
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Tokenizer: AutoTokenizer from Hugging Face Transformers
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Training Environment: Kaggle Notebook with CUDA GPU
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Batch Size: 16
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Epochs: 3–5 (based on early stopping)
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Optimizer: AdamW
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Loss Function: CrossEntropyLoss
Quantized the model for reduced memory usage and faster inference without compromising translation quality.
1model = model.half()
2model.save_pretrained("quantized_model_fp16")
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Evaluation Metric: sacrebleu on validation set
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Inference Accuracy: Verified using real-world sample sentences
