我试图遵循这篇关于AI平台上的超参数调优的教程:https://cloud.google.com/blog/products/gcp/hyperparameter-tuning-on-google-cloud-platform-is-now-faster-and-smarter。
我的配置yaml文件如下所示:
trainingInput:
hyperparameters:
goal: MINIMIZE
hyperparameterMetricTag: loss
maxTrials: 4
maxParallelTrials: 2
params:
- parameterName: learning_rate
type: DISCRETE
discreteValues:
- 0.0005
- 0.001
- 0.0015
- 0.002预期产出:
"completedTrialCount": "4",
"trials": [
{
"trialId": "3",
"hyperparameters": {
"learning_rate": "2e-03"
},
"finalMetric": {
"trainingStep": "123456",
"objectiveValue": 0.123456
},
},是否有任何方法来自定义trialId而不是默认值(例如,1、2、3、4.)?
https://stackoverflow.com/questions/68009650
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