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config.defaults.yaml
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config.defaults.yaml
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wandb:
project: acai
# Get your W&B token at https://wandb.ai/authorize
token:
kowalski:
host: kowalski.caltech.edu
port: 443
protocol: https
token:
collections:
alerts: ZTF_alerts
fritz:
token:
protocol: https
host: fritz.science
features:
"20201130":
drb:
norm: 1
diffmaglim:
norm: 1
ra:
norm: 1
dec:
norm: 1
magpsf:
norm: 1
sigmapsf:
norm: 1
chipsf:
norm: 1
fwhm:
norm: 1
sky:
norm: 1
chinr:
norm: 1
sharpnr:
norm: 1
sgscore1:
norm: 1
distpsnr1:
norm: 1
sgscore2:
norm: 1
distpsnr2:
norm: 1
sgscore3:
norm: 1
distpsnr3:
norm: 1
ndethist:
norm: 1
ncovhist:
norm: 1
scorr:
norm: 1
nmtchps:
norm: 1
clrcoeff:
norm: 1
clrcounc:
norm: 1
neargaia:
norm: 1
neargaiabright:
norm: 1
models:
acai_h:
# value of label should refer to dataset.dN.csv
label: "h"
# value should refer to features section of this config
features: "20201130"
parameters:
threshold: 0.5
# balance ratio for the prevalent class. leave null to use all available data
balance: 2.5
# balance: 1.1
weight_per_class: false
class_weight:
0: 1
1: 1
scale_features: "min_max"
test_size: 0.1
val_size: 0.1
random_state: 42
batch_size: 32
shuffle_buffer_size: 128
epochs: 100
features_input_shape:
- 25
triplet_shape:
- 63
- 63
- 3
dense_blocks: 2
dense_block_units: 64
dense_block_scale_factor: 0.5
dense_activation: "relu"
dense_dropout_rate: 0.25
conv_blocks: 2
conv_conv_layer_type: "SeparableConv2D"
conv_pool_layer_type: "MaxPooling2D"
conv_block_filters: 16
conv_block_filter_size:
- 3
- 3
conv_block_pool_size:
- 2
- 2
conv_block_scale_factor: 2
conv_dropout_rate: 0.25
head_blocks: 1
head_block_units: 16
head_block_scale_factor: 0.5
head_activation: "relu"
head_dropout_rate: 0
loss: "binary_crossentropy"
optimizer: "adam"
learning_rate: 3e-4
momentum: 0.9
monitor: "val_loss"
patience: 5
callbacks:
- "reduce_lr_on_plateau"
- "early_stopping"
save: false
sweep:
# refer to https://docs.wandb.ai/guides/sweeps
metric:
name: "val_loss"
goal: "minimize"
method: "grid"
parameters:
balance:
value: 2.5
epochs:
value: 100
patience:
value: 10
threshold:
value: 0.5
dense_block_units:
values:
- 64
- 128
- 256
conv_block_filters:
values:
- 16
- 32
- 64
head_block_units:
values:
- 16
- 32
- 64
acai_b:
label: "b"
features: "20201130"
parameters:
balance: 2.5
# balance: 1.1
weight_per_class: false
acai_o:
label: "o"
features: "20201130"
parameters:
balance: 2.5
# balance: 1.1
weight_per_class: false
acai_n:
label: "n"
features: "20201130"
parameters:
balance: 2.5
# balance: 1.1
weight_per_class: false
acai_v:
label: "v"
features: "20201130"
parameters:
balance: 2.5
# balance: 1.1
weight_per_class: false