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megs_ai_2024_config.yaml
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megs_ai_2024_config.yaml
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# Model parameters
model:
# General training parameters
epochs: [100] # If the model is not hybrid, use this value
lr: [1.e-4] # If the model is not hybrid, use this value
seed: [3110] # Seed used for training
architecture: ['hybrid']
# Training, validation, testing and holdout split
val_months: [[2, 3]] # Month used for validation
test_months: [[11, 12]] # Month used for testing
holdout_months: [[1, 10]] # Month used for holdout
# Linear model architecture
ln_epochs: [50] # Linear model epochs
ln_lr: [1.e-2] # Linear model Learning rate
# CNN architecture
cnn_model: ['efficientnet_b3'] # Choice of CNN model
cnn_lr: [1.e-4] # CNN model learning rate
cnn_dp: [0.0] # CNN model dropout rate
cnn_epochs: [50] # CNN model epochs.
# wl: # Wavelengths used as input
"94": [[0]]
"131": [[1]]
"171": [[2]]
"193": [[3]]
"211": [[4]]
"304": [[5]]
"335": [[6]]
"1600": [[7]]
"1700": [[8]]
AIA: [[0, 1, 2, 3, 4, 5, 6, 7, 8]]
EUVI: [[2, 3, 4, 5]]
EUI: [[2, 5]]
SUVI: [[0, 1, 2, 3, 4, 5]]
CIRCE: [[1, 3, 5]]
logging: 'spectrum'
# Training logging
wandb:
entity: 'trilliumtechnologies' # Name of wandb entity
project: 'SPI3S-Irradiance' # Name of wandb project
#group: 'Virtual Instrumentation' # Name of wandb group
job_type: 'Training' # Nme of wandb job_type
tags: ['development'] # Run tags
notes: "First training of linear MEGSAI model ."
wb_name: "hybrid_baseline"