('weight',0.1) :learningRate('bias',0.2)--we don't supply a weightDecay value for 'weight' --- rather we--choose to use the default value:weightDecay('bias',0) )net:add(nn.SpatialBatchNormalization(48))net:add(nn.ReLU())net:add(nn.SpatialMaxPooling(2,2,2,2))net:add(nn.View...
Thus, we set the weight decay strength to 0 in all our experiments. Increasing model sparsity rate using a cubic schedule throughout the pruning pipeline also turned out to improve accuracy for most models compared to the constant sparsity baseline (Table ...
(0.9,0.98)"--lr 0.0005\--lr-scheduler inverse_sqrt --stop-min-lr 1e-09 --warmup-updates 10000 --warmup-init-lr 1e-07 --apply-bert-init --weight-decay 0.01 \ --fp16 --clip-norm 2.0 --max-update 300000 --task translation_glat --criterion glat_loss --arch glat_sd --noise ...
Decoupled Weight Decay Regularization. International Conference on Learning Representations. 2019. Available online: https://openreview.net/forum?id=Bkg6RiCqY7 (accessed on 1 November 2022). Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those ...
The proposed model is trained for 300 epochs using AdamW optimizer [34] with weight decay 0.05, batch size 128 and peak learning rate 5 × 10−4−4. The number of linear warmup epochs is 20 with a cosine learning rate schedule. Meanwhile, typical schemes, including Mixup [35], ...