128 lines
2.1 KiB
INI
128 lines
2.1 KiB
INI
[project]
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neptune_key = eyJhcGlfYWRkcmVzcyI6Imh0dHBzOi8vdWkubmVwdHVuZS5haSIsImFwaV91cmwiOiJodHRwczovL3VpLm5lcHR1bmUuYWkiLCJhcGlfa2V5IjoiZmI0OGMzNzUtOTg1NS00Yzg2LThjMzYtMWFiYjUwMDUyMjVlIn0=
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debug = False
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eval = True
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seed = 69
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owner = si11ium
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model_name = VisualTransformer
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data_name = PrimatesLibrosaDatamodule
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[data]
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num_worker = 10
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data_root = data
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n_mels = 128
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sr = 16000
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hop_length = 128
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n_fft = 256
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sample_segment_len=50
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sample_hop_len=20
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random_apply_chance = 0.7
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loudness_ratio = 0.0
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shift_ratio = 0.3
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noise_ratio = 0.0
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mask_ratio = 0.0
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[Tester]
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weight_init = xavier_normal_
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activation = gelu
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use_bias = True
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use_norm = True
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use_residual = True
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dropout = 0.21
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lat_dim = 32
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patch_size = 8
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attn_depth = 12
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heads = 4
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embedding_size = 128
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[CNNBaseline]
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weight_init = xavier_normal_
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activation = gelu
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use_bias = True
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use_norm = True
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dropout = 0.2
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lat_dim = 32
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features = 64
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filters = [16, 32, 64, 128]
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[VisualTransformer]
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weight_init = xavier_normal_
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activation = gelu
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use_bias = True
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use_norm = True
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use_residual = True
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dropout = 0.2
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lat_dim = 32
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mlp_dim = 32
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head_dim = 32
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patch_size = 8
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attn_depth = 12
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heads = 4
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embedding_size = 33
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[VerticalVisualTransformer]
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weight_init = xavier_normal_
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activation = gelu
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use_bias = True
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use_norm = True
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use_residual = True
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dropout = 0.2
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lat_dim = 32
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patch_size = 8
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attn_depth = 12
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heads = 4
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embedding_size = 128
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[HorizontalVisualTransformer]
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weight_init = xavier_normal_
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activation = gelu
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use_bias = True
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use_norm = True
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use_residual = True
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dropout = 0.3
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lat_dim = 256
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patch_size = 8
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attn_depth = 12
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heads = 6
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embedding_size = 32
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[VisualPerformer]
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weight_init = xavier_normal_
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activation = gelu
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use_bias = True
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use_norm = True
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use_residual = True
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dropout = 0.2
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lat_dim = 32
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patch_size = 8
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attn_depth = 12
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heads = 4
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embedding_size = 30
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[train]
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outpath = output
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version = None
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sampler = EqualSampler
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loss = ce_loss
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sto_weight_avg = False
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weight_decay = 0
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opt_reset_interval = 0
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max_epochs = 150
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batch_size = 30
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lr = 0.001
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scheduler='LambdaLR'
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use_residual = True
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lr_scheduler_parameter = 0.97
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num_sanity_val_steps = 2
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check_val_every_n_epoch = 5
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checkpoint_callback = True
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gradient_clip_val = 0
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