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icc-28/.riahub/train_configs/train.yaml

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data:
batch_size: 32
dataset_params:
iq_key: iq_data
label_key: labels
drop_last: false
kind: iq_h5
num_workers: 0
persistent_workers: false
pin_memory: false
test_path: /opt/qmb/riahub/dataset/qoherent/icc-28/main/datasets/icc28-test_v1.0.0.h5
test_split: 0
train_path: /opt/qmb/riahub/dataset/qoherent/icc-28/main/datasets/icc28-train_v1.0.0.h5
validation_path: /opt/qmb/riahub/dataset/qoherent/icc-28/main/datasets/icc28-test_v1.0.0.h5
validation_split: 0
evaluation:
capture_predictions: true
enabled: true
params:
save_confusion: true
split: test
export:
dynamic_batch: true
dynamic_width: false
enabled: true
file_name: model.onnx
opset_version: 17
strict: false
use_dynamo: true
use_onnxsim: false
model:
name: iq_vtcnn2
params:
dropout_p: 0.6
optimization:
loss:
name: cross_entropy
params: {}
optimizer:
name: adam
params:
amsgrad: false
eps: 1e-08
lr: 0.001
weight_decay: 0
runtime:
amp_enabled: false
autocast_dtype: float32
checkpoint_every_n_epochs: 1
component_modules: []
device: auto
epochs: 1
progress_bar: false
seed: 42
task:
name: classification
params:
save_artifacts: true
selection_metric: accuracy
selection_mode: max