I'm trying to train a YOLOv5s model with SparseML. (I don't know if this is important, but I am training in Google Colab). When I run train.py, I get this error:
ValueError: Unable to find any modifiers in given recipe. Modifiers must be listed as lists under yaml keys that include 'modifiers' in their name. Those keys and lists may also be nested under an extra key for staged recipes.
This is my recipe.yaml:
---
layout: null
title: ETS2 vehicle Detection Dataset Recipe
---
modifiers:
- !EpochRangeModifier
start_epoch: 0.0
end_epoch: 250.0
- !SetLearningRateModifier
start_epoch: 5.0
learning_rate: 0.1
- !LearningRateModifier
start_epoch: 0.0
end_epoch: 25.0
lr_class: MultiStepLR
lr_kwargs:
gamma: 0.9
milestones: [2.0, 5.5, 10.0]
init_lr: 0.1
- !GMPruningModifier
start_epoch: 50.0
end_epoch: 100.0
update_frequency: 1.0
init_sparsity: 0.05
final_sparsity: 0.65
params: ['blocks.1.conv']
- !QuantizationModifier
start_epoch: 100.0
- !TrainableParamsModifier
params: ['blocks.1.conv']
- !SetWeightDecayModifier
start_epoch: 5.0
weight_decay: 0.0
- !ConstantPruningModifier
params: ['blocks.1.conv]
What am I doing wrong with this, and how could I resolve this issue?