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@onusozI am now training smol bert models on my gpu for @janitr_ai scam detection it's funny how I have to discover everything from scratch. like the models don't even know how to lay out performance metrics in a nice way in the terminal for a human to view and decide during experiments it would by default bombard me with numbers that do not make visual sense. I then created a skill with common sense: - metrics always on y-axis, candidates on x-axis - write without zero and 2 sigfigs,.12 instead of 0.12345 - align the dots - use asterisks to show which alternative is the best: 0-1% difference -> considered equal 1-5% -> * 5-10% -> ** 10-50% -> *** > 50% -> **** visualization skill is in @janitr_ai repo for anyone who is interested