From 3129bdb2c107e8490ef2e4aa9338787fdd27813e Mon Sep 17 00:00:00 2001 From: Ross Wightman Date: Wed, 4 Dec 2019 11:13:25 -0800 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index bd734537..6f3f4410 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ ### Dec 4, 2019 * Added weights from the first training from scratch of an EfficientNet (B2) with my new RandAugment implementation. Much better than my previous B2 and very close to the official AdvProp ones (80.4 top-1, 95.08 top-5). - * For those interested in hparams, I trained with the following: `./distributed_train.sh 2 /imagenet/ --model efficientnet_b2 -b 128 --sched step --epochs 450 --decay-epochs 2.4 --decay-rate .97 --opt rmsproptf --opt-eps .001 -j 8 --warmup-lr 1e-6 --weight-decay 1e-5 --drop 0.3 --drop-connect 0.2 --model-ema --aa rand-m9-noise0.5 --remode pixel --reprob 0.2 --amp --lr .016` + * For those interested in hparams, I trained with the following: `./distributed_train.sh 2 /imagenet/ --model efficientnet_b2 -b 128 --sched step --epochs 450 --decay-epochs 2.4 --decay-rate .97 --opt rmsproptf --opt-eps .001 -j 8 --warmup-lr 1e-6 --weight-decay 1e-5 --drop 0.3 --drop-connect 0.2 --model-ema --model-ema-decay 0.9999 --aa rand-m9-noise0.5 --remode pixel --reprob 0.2 --amp --lr .016` ### Nov 29, 2019 * Brought EfficientNet and MobileNetV3 up to date with my https://github.com/rwightman/gen-efficientnet-pytorch code. Torchscript and ONNX export compat excluded.