master_thesis_models / configs /experiment /focusConvMSE_besthyp_150.yaml
Hannes Kuchelmeister
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# @package _global_
# to execute this experiment run:
# python train.py experiment=example
defaults:
- override /datamodule: focus150.yaml
- override /model: focusConv_150.yaml
- override /callbacks: default.yaml
- override /logger: many_loggers
- override /trainer: default.yaml
# all parameters below will be merged with parameters from default configurations set above
# this allows you to overwrite only specified parameters
# name of the run determines folder name in logs
name: "focusConvMSE_150"
seed: 12345
trainer:
min_epochs: 1
max_epochs: 100
model:
image_size: 150
pool_size: 2
conv1_size: 3
conv1_channels: 9
conv2_size: 7
conv2_channels: 6
lin1_size: 32
lin2_size: 72
output_size: 1
lr: 0.001
weight_decay: 0.0005
datamodule:
batch_size: 64
augmentation: True