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First, thank you for providing your implementation, it is quite instructive.
I had a question regarding what normalization was done for MSE during evaluation - was the normalization denominator the variance(y_true) or mean((y_true)^2)?
Because the code for training uses just mse without normalization -
- https://github.com/deep-symbolic-mathematics/LLM-SR/blob/main/specs/specification_bactgrow_numpy.txt#L25
- https://github.com/deep-symbolic-mathematics/LLM-SR/blob/main/specs/specification_oscillator1_numpy.txt#L25
- https://github.com/deep-symbolic-mathematics/LLM-SR/blob/main/specs/specification_oscillator2_numpy.txt#L25
- https://github.com/deep-symbolic-mathematics/LLM-SR/blob/main/specs/specification_oscillator2_torch.txt#L38
- https://github.com/deep-symbolic-mathematics/LLM-SR/blob/main/specs/specification_stressstrain_numpy.txt
I could not find a reference to normalized mse for evaluation in this repo (though I may have missed it)
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