training schedule.toml

[fasterrcnnbaseline]
k = [1, 2, 3, 5, 10, 20, 35]
epochs = [450, 600, 700, 1050, 2200, 4000, 5000]
epochsinterval = [50, 50, 50, 50, 50, 50, 50]
epochsonlyoneloss = [300, 400, 500, 1000, 1400, 2000, 2000]
dataset = FoodQS
pretrained = false
fsdet = false
model = fasterrcnn

[mobilenetbaseline]
k = [1, 2, 3, 5, 10, 20, 35]
epochs = [400, 550, 700, 950, 2000, 3600, 4500]
epochsinterval = [50, 50, 50, 50, 50, 50, 50]
epochsonlyoneloss = [300, 300, 400, 500, 700, 900, 1000]
dataset = FoodQS
pretrained = false
fsdet = false
model = mobilenet

[mobilenet320baseline]
k = [1, 2, 3, 5, 10, 20, 35]
epochs = [400, 400, 500, 600, 1200, 1500, 1700]
epochsinterval = [50, 50, 50, 50, 50, 50, 50]
epochsonlyoneloss = [300, 300, 400, 500, 700, 900, 1000]
dataset = FoodQS
pretrained = false
fsdet = false
model = mobilenet320

[fasterrcnnfsdet]
k = [1, 2, 3, 5, 10, 20, 35]
epochs = [200, 250, 300, 500, 1100, 650, 650]
epochsinterval = [50, 50, 50, 50, 50, 50, 50]
epochsonlyoneloss = [200, 250, 300, 500, 1100, 650, 650]
dataset = FoodQS
pretrained = true
fsdet = true
model = fasterrcnn

[mobilenetfsdet]
k = [1, 2, 3, 5, 10, 20, 35]
epochs = [200, 250, 300, 500, 1000, 800, 800]
epochsinterval = [50, 50, 50, 50, 50, 50, 50]
epochsonlyoneloss = [200, 250, 300, 500, 1000, 800, 800]
dataset = FoodQS
pretrained = true
fsdet = true
model = mobilenet

[mobilenet320fsdet]
k = [1, 2, 3, 5, 10, 20, 35]
epochs = [200, 200, 250, 300, 450, 700, 800]
epochsinterval = [50, 50, 50, 50, 50, 50, 50]
epochsonlyoneloss = [200, 200, 250, 300, 450, 700, 800]
dataset = FoodQS
pretrained = true
fsdet = true
model = mobilenet320

[fasterrcnnpollen]
k = [1, 2, 3, 5, 10]
epochs = [200, 250, 300, 500, 250]
epochsinterval = [50, 50, 50, 50, 50]
epochsonlyoneloss = [200, 250, 300, 500, 250]
dataset = Pollen
pretrained = true
fsdet = true
model = fasterrcnn