Create README.md

README.md

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+## 🧠 English to Spanish Translation AI Model
+
+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.
+
+---
+
+## 🚀 Features
+
+- 🔁 **Language Pair**: English → Spanish
+- 🔧 **Model**: Helsinki-NLP/opus-mt-en-es
+- 🧪 **Quantized**: FP16 for efficient inference
+- 🎯 **High Accuracy**: Scored well on validation sets
+- ⚡ **CUDA Enabled**: Fast training and inference
+
+---
+
+## 📊 Dataset Used
+
+**Hugging Face Dataset**: **OscarNav/spa-eng**
+
+- Source: OscarNav
+- Language Pair: `en-es`
+- Dataset Size: ~107K sentence pairs
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("OscarNav/spa-eng", lang1="en", lang2="es")
+```
+
+## 🛠️ Model Training & Fine-Tuning
+
+ - Pretrained Base Model: Helsinki-NLP/opus-mt-en-es
+
+ - Tokenizer: AutoTokenizer from Hugging Face Transformers
+
+ - Training Environment: Kaggle Notebook with CUDA GPU
+
+ - Batch Size: 16
+
+ - Epochs: 3–5 (based on early stopping)
+
+ - Optimizer: AdamW
+
+ - Loss Function: CrossEntropyLoss
+
+
+## 🧪 Quantization (FP16)
+
+Quantized the model for reduced memory usage and faster inference without compromising translation quality.
+
+```python
+model = model.half() 
+model.save_pretrained("quantized_model_fp16")
+```
+
+## ✅ Scoring
+BLEU Score: ~34+
+
+ - Evaluation Metric: sacrebleu on validation set
+
+ - Inference Accuracy: Verified using real-world sample sentences