IonoBench / configs /SimVPv2Chrono.yaml
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Configs and Training files with model pth files
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data:
seq_len: 12
pred_horz: 12
batch_size: 128
shuffle: False
dataSplit: chronologicalSplit # Chronological or Stratified Refer to ~/Projects/PhD/Ionosphere/Python/Data Scripts/Preprocessing/Preprocess_Data_v3.ipynb
selectedOMNI: [1,4,5,6,9,10,11,12,13,14,16,17,19,27,28,29,30] # Check data.py
# ['F10.7', 'Dst', 'ap', 'AE', 'pc', 'SW Temp', 'SW Density', 'SW Speed', 'SW Long Angle', 'SW Lat Angle', 'Flow Pressure', 'E Field', 'Scalar B', 'BZ (GSM)', 'Year', 'Day of Year', 'Hour']
# [ 1, 4, 5, 6, 9, 10, 11, 12, 13, 14, 16, 17, 19, 27, 28, 29, 30]
model:
type: "SimVP"
input_shape: [12, 18, 72, 72] # (Time, Channels, Height, Width)
hid_S: 16
hid_T: 256
N_S: 4
N_T: 4
model_type: "gSTA"
mlp_ratio: 8.0
drop: 0.0
drop_path: 0.0
spatio_kernel_enc: 3
spatio_kernel_dec: 3
conv_in_channels: 18
conv_out_channels: 1
conv_kernel_size: [1, 1, 1]
conv_stride: [1, 1, 1]
train:
model: "SimVP" # Model to train
sessionName: "SimVP_chronologicalSplit" # Name of the session
lr: 8e-5 # Learning rate for Optimizer (LRrangetest minima at [LR=0.0001] Global average loss = 5.77232401785838e-06)
lrEnd: 5e-6 # Learning rate end for ExponentialLR
batchSize: 128 # Batch size for training
numEpochs: 50 # Number of epochs to train
resumeEpoch: 0 # Resume training from epoch
earlyStop: 10 # Early stopping patience
saveResults: True # Save results
inputNames: [] # Names of the input features
criterion: "MSELoss" # Loss functions: MSELoss.
optimizer: "Adam" # Optimizer: Adam.
scheduler: "ReduceLROnPlateau" # Scheduler: ExponentialLR, ReduceLROnPlateau
mixedPrecision: False # Mixed precision training
test:
model: "SimVP"
sessionName: "SimVP_chronologicalSplit" # Name of the session
batchSize: 128
testDates: [] # Dates to test will be set in the script
maxTEC: "210" # Set inside the main script
minTEC: "0" # Set inside the main script
lat: "72" # Set inside the main script
lon: "72" # Set inside the main script
numOMNI: "18" # Set inside the main script
inputNames: [] # Set inside the main script
saveResults: True