Training ESC from scratch with SiT-B/2 with class-consistent mini-batching, run the following
accelerate launch --multi_gpu \
train.py \
--exp-name "esc-b2-cc" \
--output-dir "exp" \
--data-dir "YOUR/DESTINATION/LMDB/PATH" \
--model "SiT-B/2" \
--resolution 256 \
--batch-size 512 \
--allow-tf32 \
--mixed-precision "bf16" \
--epochs 240 \
--path-type "linear" \
--loss-type "adaptive" \
--time-sampler "logit_normal" \
--time-mu -0.4 \
--time-sigma 1.0 \
--ratio-r-not-equal-t 0.25 \
--adaptive-p 1.0 \
--cfg-omega 1.0 \
--cfg-kappa 0.5 \
--cfg-min-t 0.0 \
--cfg-max-t 1.0 \
--variational-adaptive-weight \
--grad-warmup-steps 0 \
--use-vplug \
--vplug-prob 0.5 \
--term-zero-steps 20000 \
--class-consist \
--no-debugOr without class-consistent mini-batching:
accelerate launch --multi_gpu \
train.py \
--exp-name "esc-b2-nocc" \
--output-dir "exp" \
--data-dir "YOUR/DESTINATION/LMDB/PATH" \
--model "SiT-B/2" \
--resolution 256 \
--batch-size 512 \
--allow-tf32 \
--mixed-precision "bf16" \
--epochs 240 \
--path-type "linear" \
--loss-type "adaptive" \
--time-sampler "logit_normal" \
--time-mu -0.4 \
--time-sigma 1.0 \
--ratio-r-not-equal-t 0.25 \
--adaptive-p 1.0 \
--cfg-omega 1.0 \
--cfg-kappa 0.5 \
--cfg-min-t 0.0 \
--cfg-max-t 1.0 \
--variational-adaptive-weight \
--grad-warmup-steps 0 \
--use-vplug \
--vplug-prob 0.5 \
--term-zero-steps 20000 \
--no-class-consist \
--no-debugTraining ESC from scratch with SiT-XL/2 with class-consistent mini-batching, run the following
accelerate launch --multi_gpu \
train.py \
--exp-name "esc-xl-cc" \
--output-dir "exp" \
--data-dir "YOUR/DESTINATION/LMDB/PATH" \
--model "SiT-XL/2" \
--resolution 256 \
--batch-size 256 \
--allow-tf32 \
--mixed-precision "bf16" \
--epochs 240 \
--path-type "linear" \
--loss-type "adaptive" \
--time-sampler "logit_normal" \
--time-mu -0.4 \
--time-sigma 1.0 \
--ratio-r-not-equal-t 0.25 \
--adaptive-p 1.0 \
--cfg-omega 0.2 \
--cfg-kappa 0.92 \
--cfg-min-t 0.0 \
--cfg-max-t 0.75 \
--variational-adaptive-weight \
--grad-warmup-steps 0 \
--use-vplug \
--vplug-prob 0.2 \
--term-zero-steps 20000 \
--class-consist \
--no-debugOr without class-consistent mini-batching:
accelerate launch --multi_gpu \
train.py \
--exp-name "esc-xl-nocc" \
--output-dir "exp" \
--data-dir "YOUR/DESTINATION/LMDB/PATH" \
--model "SiT-XL/2" \
--resolution 256 \
--batch-size 256 \
--allow-tf32 \
--mixed-precision "bf16" \
--epochs 240 \
--path-type "linear" \
--loss-type "adaptive" \
--time-sampler "logit_normal" \
--time-mu -0.4 \
--time-sigma 1.0 \
--ratio-r-not-equal-t 0.25 \
--adaptive-p 1.0 \
--cfg-omega 0.2 \
--cfg-kappa 0.92 \
--cfg-min-t 0.0 \
--cfg-max-t 0.75 \
--variational-adaptive-weight \
--grad-warmup-steps 0 \
--use-vplug \
--vplug-prob 0.2 \
--term-zero-steps 20000 \
--no-class-consist \
--no-debug