BRONet_ImageNet / config.yaml
pinhank0121
BRONet for ImageNet (Table 1)
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dataset:
ddpm: false
ddpm_ratio: 0
input_size: 224
name: imagenet
num_classes: 1000
loss:
eps: 0.1411764705882353
gamma: 5.0
loss_type: logit_annealing_loss
max_eps_ratio: 2.0
min_eps_ratio: 0.1
offset: 2.0
temperature: 0.75
model:
act_name: MinMax
backbone_centering: true
backbone_type: hybridbrov2
backbone_weight_rank_ratio: 0.5
dense_type: cholesky
dense_width: 2048
depth: 14
depth_1: 6
depth_2: 8
linear_num: 8
neck_conv_patch_size: 8
neck_conv_patch_size_2: 0
neck_conv_type: l2
neck_linear_type: cholesky
num_lc_iter: 10
stem_kernel_size: 5
use_lln: true
width: 588
training:
batch_size: 1024
epochs: 400
grad_clip: true
grad_clip_val: 3
lion: false
lookahead: true
lr: 0.001
momentum: 0.0
nadam: true
sgd: false
warmup_epochs: 20
weight_decay: 0.0