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wandb_yolo_sweep.yaml
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wandb_yolo_sweep.yaml
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command:
- "srun"
- "-c"
- "16"
- "--gres=gpu:1,gpumem:24G"
- "--mem"
- "32G"
- "--time=10:00:00"
- ${env}
- yolo
- ${program}
- ${args_no_hyphens}
program: train
method: bayes
metric:
name: metrics/mAP50-95(B)
goal: maximize
parameters:
model:
value: ./DATA/yolov8n.pt
data:
value: './DATA/datasets/ant_subset_1-000+colonias_640x640_crops/ant_subset_1-000+colonias_640x640_crops.yaml'
imgsz:
value: 640
single_cls:
value: True
epochs:
value: 500
batch:
distribution: int_uniform
min: 50
max: 100
optimizer:
values: ["Adam", "SGD"]
warmup_epochs:
value: 10
lr0:
distribution: uniform
max: 0.01
min: 0.001
lrf:
distribution: uniform
max: 0.001
min: 0.0001
cos_lr:
values:
- True
- False
momentum:
distribution: uniform
max: 0.974
min: 0.9
dropout:
values: [0.0, 0.25, 0.5, 0.75]
nms:
values:
- True
- False
agnostic_nms:
value: True
iou:
distribution: uniform
min: 0.5
max: 1
hsv_h:
distribution: uniform
min: 0
max: 0.3
hsv_s:
distribution: uniform
min: 0
max: 0.5
hsv_v:
distribution: uniform
min: 0
max: 0.5
degrees:
distribution: uniform
min: 60
max: 180
translate:
distribution: uniform
min: 0
max: 0.5
scale:
distribution: uniform
min: 0
max: 1
flipud:
distribution: uniform
min: 0
max: 0.5
fliplr:
distribution: uniform
min: 0
max: 0.5
mosaic:
distribution: uniform
min: 0
max: 1
shear:
distribution: uniform
min: 0
max: 15
perspective:
distribution: uniform
min: 0
max: 0.001
mixup:
distribution: uniform
min: 0
max: 0.12
copy_paste:
distribution: uniform
min: 0
max: 1