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+experiment_group: Sample Experiments
+experiments:
+ - train_args:
+ batch_size: 64
+ max_epochs: 32
+ dataset:
+ type: EmnistLinesDataset
+ args:
+ subsample_fraction: 0.33
+ max_length: 34
+ min_overlap: 0
+ max_overlap: 0.33
+ num_samples: 10000
+ seed: 4711
+ blank: true
+ train_args:
+ num_workers: 6
+ train_fraction: 0.85
+ model: LineCTCModel
+ metrics: [cer, wer]
+ network:
+ type: LineRecurrentNetwork
+ args:
+ # encoder: ResidualNetworkEncoder
+ # encoder_args:
+ # in_channels: 1
+ # num_classes: 81
+ # depths: [2, 2]
+ # block_sizes: [64, 128]
+ # activation: SELU
+ # stn: false
+ encoder: WideResidualNetwork
+ encoder_args:
+ in_channels: 1
+ num_classes: 81
+ depth: 16
+ num_layers: 4
+ width_factor: 2
+ dropout_rate: 0.2
+ activation: selu
+ use_decoder: false
+ flatten: true
+ input_size: 256
+ hidden_size: 128
+ num_layers: 2
+ num_classes: 81
+ patch_size: [28, 14]
+ stride: [1, 5]
+ criterion:
+ type: CTCLoss
+ args:
+ blank: 80
+ optimizer:
+ type: AdamW
+ args:
+ lr: 1.e-02
+ betas: [0.9, 0.999]
+ eps: 1.e-08
+ weight_decay: 5.e-4
+ amsgrad: false
+ # lr_scheduler:
+ # type: OneCycleLR
+ # args:
+ # max_lr: 1.e-03
+ # epochs: null
+ # anneal_strategy: linear
+ lr_scheduler:
+ type: CosineAnnealingLR
+ args:
+ T_max: null
+ swa_args:
+ start: 4
+ lr: 5.e-2
+ callbacks: [Checkpoint, ProgressBar, WandbCallback, WandbImageLogger, SWA] # EarlyStopping, OneCycleLR]
+ callback_args:
+ Checkpoint:
+ monitor: val_loss
+ mode: min
+ ProgressBar:
+ epochs: null
+ log_batch_frequency: 100
+ # EarlyStopping:
+ # monitor: val_loss
+ # min_delta: 0.0
+ # patience: 5
+ # mode: min
+ WandbCallback:
+ log_batch_frequency: 10
+ WandbImageLogger:
+ num_examples: 6
+ # OneCycleLR:
+ # null
+ SWA:
+ null
+ verbosity: 1 # 0, 1, 2
+ resume_experiment: null
+ test: true
+ test_metric: test_cer