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katib/examples/v1beta1/early-stopping/median-stop-with-json-format.yaml
Mahdi KhashanandGitHub 19db2d47d4 [feature] move manifest image references to ghcr (#2529)
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Signed-off-by: mahdikhashan <[email protected]>
Signed-off-by: Mahdi Khashan <[email protected]>
2025-03-24 17:11:50 +00:00

74 lines
1.9 KiB
YAML

---
# This is example with median stopping early stopping rule with logs in JSON format.
# It has bad feasible space for learning rate to show more early stopped Trials.
apiVersion: kubeflow.org/v1beta1
kind: Experiment
metadata:
namespace: kubeflow
name: median-stop-with-json-format
spec:
objective:
type: maximize
goal: 0.99
objectiveMetricName: accuracy
additionalMetricNames:
- loss
metricsCollectorSpec:
source:
fileSystemPath:
path: "/katib/mnist.json"
kind: File
format: JSON
collector:
kind: File
algorithm:
algorithmName: random
earlyStopping:
algorithmName: medianstop
algorithmSettings:
- name: min_trials_required
value: "1"
- name: start_step
value: "2"
parallelTrialCount: 2
maxTrialCount: 15
maxFailedTrialCount: 3
parameters:
- name: lr
parameterType: double
feasibleSpace:
min: "0.01"
max: "0.5"
- name: num-epochs
parameterType: int
feasibleSpace:
min: "3"
max: "4"
trialTemplate:
retain: true
primaryContainerName: training-container
trialParameters:
- name: learningRate
description: Learning rate for the training model
reference: lr
- name: numberEpochs
description: Number of epochs to train the model
reference: num-epochs
trialSpec:
apiVersion: batch/v1
kind: Job
spec:
template:
spec:
containers:
- name: training-container
image: ghcr.io/kubeflow/katib/pytorch-mnist-cpu:latest
command:
- "python3"
- "/opt/pytorch-mnist/mnist.py"
- "--epochs=${trialParameters.numberEpochs}"
- "--log-path=/katib/mnist.json"
- "--lr=${trialParameters.learningRate}"
- "--logger=hypertune"
restartPolicy: Never