AI Model Training Monitor

Training Compute

Production does not need a GPU. Training runs on a registered compute agent.

No AI Compute Devices

Your production server does not have a compatible GPU, or no external compute device has been registered.

Click + Register This Device, then run the printed commands from apps/sdrra-ai-worker (system Python at the repo root has no sdrra_worker module). Browser sessions never become training nodes.

Compute Selection Mode

Local FastAPI monitor is idle — use Training Compute above for remote GPU jobs

  • Production Render AI has no CUDA GPU. Dispatch training to a registered compute agent.
  • Closing the browser does not stop a remote job — the agent keeps heartbeating to the API.
  • After training, deploy best.pt to Render via YOLO_WEIGHTS_URL or the model registry.
Epoch
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ETA
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Idle
GPU Usage
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No CUDA device
VRAM
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Speed
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Est. from dataset Ă— epochs
Best mAP@50
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—
Current Loss
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Training Status
Idle
Waiting…

Dataset Overview

Training Images—
Validation Images—
Test Images—
Classes—
Annotations (est.)—
Avg. / Image—

Class Distribution

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  • Class counts appear after the AI training config loads a dataset.

Training Metrics (Live)

Box Loss
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Cls Loss
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DFL Loss
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mAP@50
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Precision
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Recall
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F1 Score
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Learning Rate
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Training Console

Idle
No console output yet.Output appears here once you run python train.py

System Monitor

GPU—
VRAM—
CPU—
RAM—

Notifications

  • Start a run to see events

Data Augmentation Preview

Original
Rotation
Brightness
Blur
Mosaic
MixUp
HSV

Prediction Preview

Ground Truth
Pending
Prediction
Pending
Overlay
Pending
Heatmap
Pending
Confidence
  • mAP@50—
  • Precision—
  • Recall—
  • F1—

Confusion Matrix

Generates after validation

Precision-Recall Curve

Generates after validation

Best Checkpoints

EpochmAPP / RAct
No checkpoint yet

Model Comparison

ModelmAPPR
Current run———

Training Controls

Export Model

Quick Actions

Experiment Info