Hi Mohammad, the new project is actually running fine.
I am logging the metrics from the sci-kit learn classification_report for my testSets
classification_report1 = classification_report(allLabels,allPredixs, output_dict=True)
prediction_time = time.perf_counter()
accuracy = accuracy_score(allLabels,allPredixs)
if(self.wandbSwitch):
api = wandb.Api()
run = api.run(self.wandbApiUUID)
print(“ALL KEYS”,run.summary.keys())
for key in classification_report1[‘non_shaky’]:
run.summary[f’testSet_{testSetName[testSetIndex]}.classification_report.non_shaky.{key}'] = classification_report1[‘non_shaky’][key]
print(f’testSet_{testSetName[testSetIndex]}.classification_report.non_shaky.{key}: ',classification_report1[‘non_shaky’][key])
for key in classification_report1[‘shaky’]:
run.summary[f’testSet_{testSetName[testSetIndex]}.classification_report.shaky.{key}'] = classification_report1[‘shaky’][key]
print(f’testSet_{testSetName[testSetIndex]}.classification_report.shaky.{key}: ',classification_report1[‘shaky’][key])
run.summary[f"testSet_{testSetName[testSetIndex]}.Prediction"] = prediction_time-start_time
run.summary[f"testSet_{testSetName[testSetIndex]}.Test Error Rate"] = round((1-accuracy)*100, 2)
run.update()
run.summary.update()
I created a new project under the name “japi-tuc” however I ran into the same problem, there are only 44 runs however almost 130 charts were created.
I understand that when deleting charts they are sent to the hidden_charts section.
However even when I delete the chart and they are in the hidden_charts section, it seems almost impossible to load the project table still.
It is taking over 6 minutes to load the project table with just 40 runs.
Please let me know if there is a way around this !
Kind regards,
Japinder