Run pipeline

[nschenone]

This will run pipelines and report back

[nschenone]

/run train --arguments label_column=target --arguments test_size=0.2

[github-actions[bot]]

Pipeline started in project berkeley-mlops id=b450517b-6cc0-4206-b4d4-687c32dd1c98, commit=ae46071f355f81e466a6ba403f50d0e503e27a93

click here to view progress

[github-actions[bot]]

Run Results

Workflow b450517b-6cc0-4206-b4d4-687c32dd1c98 finished, state=Succeeded
click the hyper links below to see detailed results

uid	start	state	name	parameters	results
...9f04e081	Sep 06 20:46:23	completed	train-model-train_model	label_column=target test_size=0.2	accuracy=1.0 f1_score=1.0 precision_score=1.0 recall_score=1.0 auc-micro=1.0 auc-macro=1.0 auc-weighted=1.0
...045b7792	Sep 06 20:46:02	completed	get-data-prep_data	label_column=target	num_rows=150

[nschenone]

/run train --arguments label_column=target --arguments test_size=0.2

[github-actions[bot]]

Pipeline started in project berkeley-mlops id=40c30f23-8d73-4de3-b0b9-afa5dae3fc1f, commit=065265329232d59ec0a9849f5393aa0b06827196

click here to view progress

[github-actions[bot]]

Run Results

Workflow 40c30f23-8d73-4de3-b0b9-afa5dae3fc1f finished, state=Succeeded
click the hyper links below to see detailed results

uid	start	state	name	parameters	results
...662d613a	Sep 06 21:14:16	completed	train-model-train_model	label_column=target test_size=0.2	accuracy=1.0 f1_score=1.0 precision_score=1.0 recall_score=1.0 auc-micro=1.0 auc-macro=1.0 auc-weighted=1.0
...68ddab6e	Sep 06 21:13:54	completed	get-data-prep_data	label_column=target	num_rows=150