Timm - efficientnetv2_s

[StrongTanisha]

Source / repo

[URL]

Model description

[DESCRIPTION]

Dataset

[DATASET]

Literature benchmark source

https://arxiv.org/abs/2104.00298

Literature benchmark performance

[DESCRIPTION]
[VALUE/S]
https://github.com/huggingface/pytorch-image-models/blob/main/results/results-imagenet.csv#:~:text=tf_efficientnetv2_s.in1k

Strong Compute result achieved

[VALUE/S]

Basic training config (as applicable)

Nodes: 12
Epochs: 350
Effective batch size: [N]
Learning rate: [L]
Optimizer: [OPT]

Logs gist

[URL]

[StrongBec]

Failed - the XL and S were saving to the same checkpoint file

experiment_name="timm-efficientnetv2_s"
gpu_type="24GB VRAM GPU"
nnodes = 11
venv_path = "/mnt/Client/Strongzpnpupxvdfdllpjvckewupy3re/becstrlaxex7elmnesblpq7jurqemkbu/.venv/bin/activate"
output_path = "/mnt/Client/Strongzpnpupxvdfdllpjvckewupy3re/becstrlaxex7elmnesblpq7jurqemkbu/output_timm"
command = "train_cycling.py /mnt/.node1/Open-Datasets/imagenet/ILSVRC/Data/CLS-LOC --model=efficientnetv2_s --weight-decay=1e-5 --decay-rate=0.03 --decay-epochs=2.4 --bn-momentum=0.99 --epochs=350 --lr=0.256 --batch-size=62 --amp --resume $OUTPUT_PATH/small_checkpoint.pt"