Expand the Evaluation details section and select View report.
- Model Version Details
- Key Metrics
- Metrics
- Performance Charts
- Actions
Model Version Details
Lists down all the details of the model version, training, and evaluation jobs.
Property | Description |
---|---|
Model version ID | Specifies the model version ID. You can select the Model version ID link to go to the Model Version lifecycle page. |
Evaluation job ID | Specifies the evaluation job ID. You can select the Job ID link to go to the Job's details. |
Evaluation date | Specifies the evaluation date. |
Dataset ID | Displays the training dataset ID used to train the job. You can select the Dataset ID link to see the dataset details. |
Dataset name | Displays the training dataset name used to train the job. |
Hyper parameters | Specifies the hyper parameters defined to run the job. |
Key Metrics
Displays the key metrics that you mark in the Metrics area. The Metrics area can contain a large list of performance metrics. You can mark some of the metrics as Key Metrics to easily access them. All the key metrics will display in this area.
Metrics
Lists down the performance metrics and their values for the current model version. Use the Mark as Key Metric option to mark the key metrics and they will display in the Key Metrics area.
A list of common performance metrics is:
Metric | Description |
---|---|
Accuracy | The ratio of the number of correct predictions to the total number of input samples. |
Recall | The number of correct positive results divided by the number of all relevant samples (all samples that should have been identified as positive). |
Precision | The number of correct positive results divided by the number of positive results predicted by the classifier. |
F1-score | The Harmonic Mean between precision and recall. The range for F1 Score is (0,1). It tells you how precise your classifier is (how many instances it classifies correctly), as well as how robust it is (it does not miss a significant number of instances). |
Performance Charts
Displays a number of performance charts based on different metrics to help you monitor model performance visually and decide if you want to mark the model as Champion.
Actions
Use the model evaluation report to perform any of the following actions on the current model version.
Action | Description |
---|---|
Approve | See Approving a Model Version. |
Reject | See Rejecting a Model Version. |
Mark/Unmark as Champion | Lets you mark/unmark the model version as Champion based on its performance. For details, see Marking a Model Version as Champion. |
View model drift | Displays the Model drift page where you can monitor the model performance. For details, see Drift Monitoring. |