Experiments
The screen that collects MLflow experiments and runs by project, compares runs, and shows the metrics, parameters and artifacts of one run
Required permission: View
This screen collects the records (runs) left by each training. Whether a run came from platform training or was logged to MLflow from your own PC, every record of the same tenant ends up here. ML engineers mainly use it to compare results and register a good run in the model registry.
Records are grouped as project → experiment → run. The project comes from an MLflow experiment tag; experiments without the tag are grouped under default.
Experiment list
| # | Area | Description |
|---|---|---|
| ① | Search | Filter by experiment name or run id. |
| ② | Compare (비교) | Enabled when two or more runs are checked. The number in parentheses is how many you selected. |
| ③ | Experiment | Experiment name and number of runs. The trash icon on the right deletes the experiment (develop). |
| ④ | Compare selection | Pick a run for comparison. You can pick runs from different experiments. |
| ⑤ | Run | Name, status, headline metric, start time. Click the name to open the run detail. Runs created by platform training get a Training (학습) link that goes straight to the training run detail. |
Compare runs
Shows two or more runs side by side. Cells whose values differ are highlighted in yellow.
| # | Area | Description |
|---|---|---|
| ① | Tabs | Overview (개요) (status, start time), Metrics (메트릭), Parameters (파라미터), Charts (그래프). |
| ② | Show differences only (차이만 보기) | Hides rows whose value is the same in every run. |
| ③ | Comparison table | The first column is the metric or parameter name; the other columns are runs (short id). |
The Charts (그래프) tab overlays the runs' curves on one chart per metric. Use the enlarge icon at the top right of a chart to view it larger.
Run detail
| # | Area | Description |
|---|---|---|
| ① | Summary | Run name and status, experiment ID, start and end, duration, number of metrics. |
| ② | Actions | Register model (모델 등록) (model_register, finished runs only), Stop (중지) (develop, running runs only), Delete (삭제) (develop, finished runs only). |
| ③ | Tabs | Overview (개요) (final metrics, parameters), Metrics (메트릭) (charts), Parameters (파라미터) (search), Tags (태그), Artifacts (아티팩트) (file browser). |
The Metrics (메트릭) tab shows every logged metric as a small chart. Click a chart to switch to the single (단일) view, which also shows the last, min, max, mean and number of steps.
The Artifacts (아티팩트) tab shows the files the run uploaded (weights, result images, logs) as a tree. Select a file to see a preview on the right (image, text, JSON, first 200 rows of a CSV), and use Download all (전체 다운로드) to get everything as a zip.
Main tasks
- In the experiment list, check two or more runs to compare and press Compare (비교).
Experiments — ① search ② Compare (two or more selected) ③ experiment ④ select a run to compare ⑤ run name (opens detail) - On the Metrics (메트릭) tab, use Show differences only (차이만 보기) to see only the metrics that differ.
Compare runs — ① Overview, Metrics, Parameters and Charts tabs ② show differences only ③ values per run (differences highlighted) - Open the best run and press Register model (모델 등록). Enter a model name and press Register (등록); the new version goes into Staging. Registering again under the same name increments the version number.
Register to the model registry — the new version enters Staging
Model registration looks for the model file in the run's artifacts — in the order model logged with MLflow → model/ folder → weights/best.pt, and uses the first one found.
Statuses and badges
| Badge | Value | Meaning |
|---|---|---|
| Running (실행 중) | RUNNING | Training is in progress and metrics are accumulating. |
| Finished (완료) | FINISHED | Ended normally. Models can be registered only in this state. |
| Failed (실패) | FAILED | Ended with an error. |
| Killed (중단됨) | KILLED | Stopped by a user, or ended because platform training was stopped or interrupted. |
| Scheduled (예약됨) | SCHEDULED | Not started yet. |