File size: 2,286 Bytes
a20151e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
WANDB_MODE=online CUDA_VISIBLE_DEVICES=4 python src/imagenet/train_model.py \
    --lr 0.0005 --epochs 300 --batch-size 256 --seed 0 --position-embeddings "learnable"\
    --num-shared-experts 0 --num-routed-experts 4  --topk 4\
    --wandb-project "LMC-Attention" --wandb-group "ViT-ImageNet-MoE" --wandb-entity "vinh-bui0512-hcmut"\
    --save-dir /mnt/data/vinhbk/weights/imagenet --data-path /mnt/data/vinhbk/datasets/imagenet 

WANDB_MODE=online CUDA_VISIBLE_DEVICES=5 python src/imagenet/train_model.py \
    --lr 0.0005 --epochs 300 --batch-size 256 --seed 0 --position-embeddings "rope"\
    --num-shared-experts 0 --num-routed-experts 4  --topk 4\
    --wandb-project "LMC-Attention" --wandb-group "ViT-ImageNet-MoE" --wandb-entity "vinh-bui0512-hcmut"\
    --save-dir /mnt/data/vinhbk/weights/imagenet --data-path /mnt/data/vinhbk/datasets/imagenet 

WANDB_MODE=online CUDA_VISIBLE_DEVICES=3 python src/imagenet/train_model.py \
    --lr 0.0005 --epochs 300 --batch-size 256 --seed 0 --position-embeddings "rope"\
    --num-shared-experts 1 --num-routed-experts 0  --topk 0\
    --wandb-project "LMC-Attention" --wandb-group "ViT-ImageNet-FFN" --wandb-entity "vinh-bui0512-hcmut"\
    --save-dir /mnt/data/vinhbk/weights/imagenet --data-path /mnt/data/vinhbk/datasets/imagenet 

# WANDB_MODE=online CUDA_VISIBLE_DEVICES=2,3 python src/imagenet/train_model.py \
#     --lr 0.0005 --epochs 300 --batch-size 256 \
#     --seed 0 --position-embeddings "sinusoidal"\
#     --wandb-project "LMC-Attention" --wandb-group "ViT-ImageNet-FFN" --wandb-entity "vinh-bui0512-hcmut"\
#     --save-dir /mnt/data/vinhbk/weights/imagenet --data-path /mnt/data/vinhbk/datasets/imagenet\
#     --restore-checkpoint-path /mnt/data/vinhbk/weights/imagenet/lr0.0005-sinusoidal-epochs300-batch256/last_1170936

# WANDB_MODE=online CUDA_VISIBLE_DEVICES=4,5 python src/imagenet/train_model.py \
#     --lr 0.0005 --epochs 300 --batch-size 256 --seed 0 --position-embeddings "rope"\
#     --wandb-project "LMC-Attention" --wandb-group "ViT-ImageNet-MoE" --wandb-entity "vinh-bui0512-hcmut"\
#     --save-dir /mnt/data/vinhbk/weights/imagenet --data-path /mnt/data/vinhbk/datasets/imagenet \
#     --restore-checkpoint-path /mnt/data/vinhbk/weights/imagenet/lr0.0005-rope-epochs300-batch256/last_300240