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logs/README.md

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+# Definition of terms and hyperparameters in configs
+
+Data-driven models are indicated by the `_s2s` suffix (e.g., `unet_s2s`). In addition, within each data-driven model, the checkpoints and hyperparameter specifications are located within the `version_xx/lightning_logs`. The hyperparameters specify the following:
+
+- `lead_time` (default: 1): arbitrary delta_t to finetune the model, for direct approach
+- `n_step` (default: 1): number of autoregressive step, s, for autoregressive approach
+- `only_headline`: if false, optimize for task 1; if true for task 2
+- `batch_size`: the batch size used for training
+- `train_years`: list of years used for training
+- `val_years`: list of years used for validation
+- `epochs`: number of epoch
+- `input_size`: number of input channel
+- `learning_rate`: update step at each iteration
+- `model_name`: the name of the model used for consistency
+- `num_workers`: number of workers used in dataloader
+- `output_size`: number of output channel
+- `t_max`: number of cosine learning rate scheduler cycle
+
+In addition, in all models, there is a folder named `eval`. This contains individual `.csv` files for each metric (e.g., SpecDiv, RMSE). Within each file, it contains scores for all channels in question (e.g., the entire 60 for task 1, arbitrary n for task 2, or 48 for physics-based models) across 44-day lead time.
+

logs/climatology/eval/acc_climatology.csv

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logs/climax/eval/direct_1/sdiv_climax.csv

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logs/climax/eval/direct_1/ssim_climax.csv

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logs/climax/eval/direct_2/rmse_climax.csv

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logs/climax/eval/direct_2/sdiv_climax.csv

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logs/climax/eval/direct_2/sres_climax.csv

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logs/climax/eval/direct_2/ssim_climax.csv

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logs/cma/eval/acc_cma.csv

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logs/cma/eval/sdiv_cma.csv

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logs/ecmwf/eval/ssim_ecmwf.csv

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