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[ARTICLE · art-54715] src=discuss.huggingface.co ↗ pub= topic=machine-learning verified=true sentiment=↓ negative

Lstm in c++/training tips

A developer reports issues with their LSTM implementation in C++, noting that training error initializes around 4.5 but can spike into the 20s, which they have not seen with other networks. They suspect a matrix indexing swap and indicate they may stop ML programming due to hardware limitations.

read1 min views1 publishedJul 10, 2026

i think there’s an issue with my implementation since my experience is disparate with others. unfortunately i hid my second post by using an out of fashion expression. it might read better for people with wider monitors than i. (or it’s in rnn-lstm.h at git hub. com/atomictraveller/scary-mess )

must be negative log likelihood as training often initialises around 4.5. “my lstm” can send error into the 20s and up which i don’t think i’ve seen before with any net. i have toxostomas that tweet when i think about math or sleep heheh.

which explains why [j][i] is swapped i think this is as far as i go with ML programming, i enjoy generation, my hardware in a number of senses is probably better scaled for procedural development.

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