> ## Documentation Index
> Fetch the complete documentation index at: https://starforge.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Job detail
> The eight tabs on a running or finished job, and which one answers which question.
Open any job from the [job list](/en/console/jobs). Eight tabs, each answering a different question.
## The tabs
| Tab | The question it answers |
| --------------- | ------------------------------------------------------------------------- |
| **Charts** | Is it learning? Loss, reward, KL, gradient norm, entropy |
| **Validation** | What is it actually producing? Sample conversations and reward histograms |
| **System** | Is the hardware healthy? GPU utilisation, memory, network, per node |
| **Config** | What exactly was submitted? Resolved config and hyperparameters |
| **Logs** | What is it saying? The full stream, searchable and downloadable |
| **Environment** | What was it running in? Package versions, CUDA, GPU models, image digest |
| **Artifacts** | What did it produce? Checkpoints, exports, evaluation reports |
| **Diagnosis** | Why does this look wrong? An automated analysis, where enabled |
## Charts
Which curves appear is not a console decision — the recipe declares them in its metric contract, and
the first two go on the overview chart. That is why two methods show different defaults and why a
framework rename does not silently blank a chart.
Empty charts with moving logs means reporting is not happening, not that training is broken. See
[reporting from training code](/en/api-reference/ingest).
## Validation
Sample conversations with their rewards, plus the distribution. Algorithm-specific fields — a DPO
rejected completion, an SFT reference answer — appear alongside without the platform needing to know
what they are.
Reading the histogram is often faster than reading the reward curve: a mean that is climbing while
the distribution splits into two clumps usually means the model found one easy subset and stopped
improving on the rest.
## Diagnosis
Runs automatically on failure and on a schedule while training, if the deployment enables it. Each
finding carries a confidence level, and a proposal may come with a **submit plan** — a concrete
follow-up job you approve or reject.
Approving a plan submits a real training job and spends real quota. The dialog says so; read the
diff before approving.
## What you can do
| Action | Effect |
| ------------ | --------------------------------------------------------------------- |
| **Pause** | Stops the job, keeping its checkpoint. Resuming continues from it |
| **Resume** | Restarts from the latest checkpoint under the same run id |
| **Stop** | Ends the run. SIGTERM first, with a grace period to save a checkpoint |
| **Share** | Creates a read-only public link — see [sharing](/en/console/sharing) |
| **Diagnose** | Runs an analysis now rather than waiting for the schedule |