Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+tags:
+- regression,
+- pytorch
+---
+
+## Model Description
+
+`NumAdd-v1.0` is a lightweight feed-forward neural network (FNN) implemented in PyTorch for numerical sum prediction.
+**Architecture:** 2-input, 1-output, with two hidden layers (32, 64 neurons) and ReLU activations.
+**Parameters:** 2,273 trainable.
+
+## Evaluation
+
+Benchmarked on 100,000 samples across five input magnitude ranges. Metrics: MAE, MSE, RMSE, R2.
+
+| Range (Input Max) | MAE     | MSE      | RMSE    | R2      |
+|-------------------|---------|----------|---------|---------|
+| 0-50              | 0.003   | 0.000    | 0.004   | 1.000   |
+| 51-500            | 0.003   | 0.000    | 0.004   | 1.000   |
+| 501-5000          | 0.004   | 0.000    | 0.006   | 1.000   |
+| 5001-50000        | 0.016   | 0.003    | 0.050   | 1.000   |
+| 50001-50000000    | 13.030  | 2295.105 | 47.907  | 1.000   |
+
+## Limitations
+
+Performance degrades significantly for large magnitude inputs (>50,000), evidenced by increased MAE/MSE, despite maintaining high R2.