To view your project’s training metrics, go to Neural Network and select the training model. Select Download to download the training metrics.
| Metric | Description | Possible range |
|---|
| Total loss | The current value of the loss function as described in Mask RCNN, a paper by Kalming He et. al. | Any range |
| Mask loss | The current value of the component of the total loss function that is responsible for the mask head. | Any range |
| Classes loss | The current value of the component of the total loss function that is responsible for the classes head. | Any range |
| Bounding box loss | The current value of the component of the total loss function that is responsible for the bounding box head. | Any range |
| Bounding box mAP | The mean average precision of the bounding boxes over all the training classes evaluated on the validation set. | 0-100 |
| Bounding box mAP at IoU=0.50 | The mean average precision of bounding boxes at IoU=0.5 evaluated on the validation set. | 0-100 (per each IoU) |
| Bounding box mAP at IoU=0.75 | The mean average precision of bounding boxes at IoU=0.75 evaluated on the validation set. | 0-100 (per each IoU) |
| Bounding box mAP for | The average precision of bounding boxes found for particular class, i.e., how precise the model was for a given class. It is reported for all the training classes. | 0-100 |
| Segmentation mAP | The mean average precision of the segmentation over all the training classes. | 0-100 |
| Segmentation mAP at IoU=0.50 | The mean average precision of segmentation at IoU=0.5 | 0-100 |
| Segmentation mAP at IoU=0.75 | The mean average precision of segmentation at IoU=0.75 | 0-100 |
| Segmentation mAP for | The average precision of the segmentation found for a particular class, i.e., how precise the model was for a given class. | 0-100 |
| ETA | Estimated time of arrival | |
| Metric | Description | Possible range |
|---|
| Total loss | The current value of the loss function as described in Mask RCNN, a paper by Kalming He et. al. | Any range |
| Classes loss | The current value of the component of the total loss function that is responsible for the classes head. | Any range |
| Bounding box loss | The current value of the component of the total loss function that is responsible for the bounding box head. | Any range |
| Bounding box mAP | The mean average precision of the bounding boxes over all the training classes evaluated on the validation set. | 0-100 |
| Bounding box mAP at IoU=0.50 | The mean average precision of the bounding boxes over all the training classes at IoU=0.50 evaluated on the validation set. | 0-100 (per each IoU) |
| Bounding box mAP at IoU=0.75 | The mean average precision of the bounding boxes over all the training classes at IoU=0.75 evaluated on the validation set. | 0-100 (per each IoU) |
| Bounding box mAP for | The average precision of the bounding boxes found for a particular class, i.e., how precise the model was for a given class. It is reported for all the training classes. | 0-100 |
| ETA | Estimated time of arrival | |
| Metric | Description | Possible range |
|---|
| Semantic segmentation loss | Pixel-wise cross entropy loss | Any value |
| ETA | Estimated time of arrival | Any value |
| mIOU | Mean intersection over union over all the classes | 0-100 |
| mACC | Mean accuracy over all the classes | 0-100 |
| ACC | Accuracy per class | 0-100 |
