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