All of these methods are optional. If the relative learning rate or weight decay is not set for a module, it will default to 1. Additionally, each method returns the original module, allowing for chaining. Rather than suppling a scalar learning rate and weight decay to the optimization functi...
(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 ...
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 ...
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], ...