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README.md

@@ -34,3 +34,39 @@ question = "translate natural language to SQL: show all customers"
 inputs = tokenizer(question, return_tensors="pt")
 output = model.generate(**inputs)
 print(tokenizer.decode(output[0], skip_special_tokens=True))
+
+
+📊 Training Details
+Epochs: 3
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+Batch Size: 8
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+Learning Rate: 5e-5
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+Optimizer: AdamW
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+Loss Function: Cross Entropy
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+Logged with: Weights & Biases
+
+📁 Files
+pytorch_model.bin or model.safetensors: The fine-tuned model
+
+tokenizer_config.json, spiece.model: Tokenizer files
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+config.json: Model architecture
+
+🚀 Intended Use
+Educational and experimental use
+
+Translate natural language questions into basic SQL queries
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+📌 Limitations
+Trained on a very small custom dataset; not production ready
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+Limited SQL syntax understanding
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+May not generalize to unseen database schemas or complex queries
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+📜 License
+Apache 2.0