[WIP] Standard baseline configs#324
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Couple of quick thoughts.
Looking at 7 days seems sensible anyway, as you can then get an idea of how the forecast accuracy develops over time. (And as you say it is more likely to beat persistence). As we've discussed a bit elsewhere (#323), doing a bit of work to optimise the models before we do this seems sensible. E.g. Erin's trained ViT model (https://wandb.ai/turing-seaice/evaluate/runs/0r9jomqk) does beat persistence |
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For reference, @erinuclkwon's model was using n_forecast_steps: 7
n_history_steps: 3which is what the next round of testing will use. |
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This PR adds some baseline configs for the model comparisons discussed in #323.
TL;DR
persistenceon a two day forecast (perhaps we want to look at e.g. 7 days?)piecewiseandvitthat make me feel that we could better-optimise these defaultsModels
00: naive-unet-naive
01: persistence
02: cnn-unet-cnn
03: cnn-vit-cnn
04: ddpm
05: piecewise-unet-piecewise-5336004.out
Metrics
RMSE
SIE Error
MAE