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dataset: EmnistDataset
dataset_args:
sample_to_balance: true
subsample_fraction: 0.33
transform: null
target_transform: null
seed: 4711
data_loader_args:
splits: [train, val]
shuffle: true
num_workers: 8
cuda: true
model: CharacterModel
metrics: [accuracy]
network_args:
in_channels: 1
num_classes: 80
depths: [2]
block_sizes: [256]
train_args:
batch_size: 256
epochs: 5
criterion: CrossEntropyLoss
criterion_args:
weight: null
ignore_index: -100
reduction: mean
optimizer: AdamW
optimizer_args:
lr: 1.e-03
betas: [0.9, 0.999]
eps: 1.e-08
# weight_decay: 5.e-4
amsgrad: false
lr_scheduler: OneCycleLR
lr_scheduler_args:
max_lr: 1.e-03
epochs: 5
anneal_strategy: linear
callbacks: [Checkpoint, ProgressBar, EarlyStopping, WandbCallback, WandbImageLogger, OneCycleLR]
callback_args:
Checkpoint:
monitor: val_accuracy
ProgressBar:
epochs: 5
log_batch_frequency: 100
EarlyStopping:
monitor: val_loss
min_delta: 0.0
patience: 3
mode: min
WandbCallback:
log_batch_frequency: 10
WandbImageLogger:
num_examples: 4
OneCycleLR:
null
verbosity: 1 # 0, 1, 2
resume_experiment: null
train: true
validation_metric: val_accuracy
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