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2026-06-12 11:42:26 -04:00
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examples/meter-detection/README.md
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@@ -153,6 +153,14 @@ Or pass the job name explicitly:
qc-cli train status qc-cli-YYYYMMDD-HHMMSS
```
To wait for completion and automatically import metrics and register the model, run:
```bash
qc-cli train wait
```
The default polling interval is 30 seconds. It can be changed with `--poll-interval <seconds>`.
## SageMaker Outputs
When the job completes, SageMaker packages the files written under `/opt/ml/model` into `model.tar.gz`.
@@ -163,10 +171,13 @@ This example writes:
best.pt
model.onnx
metrics.json
training_metrics.json
```
The archive is stored under the configured `s3.model_prefix`.
During MLflow finalization, `training_metrics.json` provides per-epoch training and validation losses, precision, recall, mAP@0.50, mAP@0.50:0.95, and learning rates. For object detection, mAP and precision/recall are more meaningful than classification accuracy when assessing model quality.
## 6. Configure Qualcomm AI Hub
Authenticate with Qualcomm AI Hub: