Metrics · AI Engineering

The metrics this manual reads, with their range on our setup.

The ranges come from our lab runs: Qwen3-0.6B on GSM8K on one GB10, 32 prompts with 8 answers each, a limit of 1,024 tokens. They hold for that setup. Build your own ranges from two or three seeds of yours.

Rollout

Metric	Meaning	Our range
`rollout/raw_reward`	the mean reward of the step	0.53 to 0.87 per step over 48 steps
`rollout/response_lengths`	the mean answer length in tokens	396 to 787
`rollout/truncated`	the share of answers that hit the length limit	0.02 to 0.43

Training

Metric	Meaning	Our range
`train/train_rollout_logprob_abs_diff`	the mean absolute gap between the trainer and engine log probabilities, per token	0.0136 to 0.0164 with plain sampling
`train/train_rollout_kl`	the KL between the engine and trainer distributions at the sampled tokens	0.00063 to 0.00076
`train/grad_norm`	the gradient norm	0.35 to 4.95
`train/pg_clipfrac`	the share of tokens where the update hit the clip limit	0 at every step
`train/ppo_kl`	the KL between the old and the new trainer probabilities	0 at step 0 in a healthy run
`train/entropy_loss`	the entropy term of the loss	0 in our runs

Time

Metric	Meaning	Our value
`perf/step_time`	the full step	152.6 s median of 48 steps, in a run made before the heat guard
`perf/rollout_time`	the rollout phase	47.5 s median of 48 steps, in a run made before the heat guard
`perf/log_probs_time`	the trainer scoring of the samples	23.4 s median of 48 steps, in a run made before the heat guard
`perf/train_time`	the training phase, with the scoring	100.3 s median of 48 steps, in a run made before the heat guard
`perf/update_weights_time`	the copy of new weights into the engine	0.63 to 0.65 s for Qwen3-0.6B
`perf/sleep_time`	the trainer moving its state to host memory after training	0.76 s median over 48 steps for Qwen3-0.6B, and 1.9 to 3.7 s in the first two steps of the same 48-step run
`perf/wake_up_time`	the trainer moving its state back before the log probabilities	0.87 s median over 48 steps for Qwen3-0.6B
`perf/train_wait_time`	the time the trainer waits for samples	logged in every step

Time values hold only for steps that no heat-guard pause touched. The lab notes give the rule.

Evaluation and async

Metric	Meaning
`eval/lag_steps`	how many steps late an eval on a dedicated fleet finished
the weight version statistics in the rollout metrics	how old the samples of an async run are

We did not run evaluation or async training, so this table has no ranges.

Sources: capture/gpu/summary/miles-gb10-lab.json (runs.plain-48, runs.plain-48-s2, runs.plain-48-s3, runs.e4-0.6b); capture/gpu/out-gb10/thermostat.log; Miles loss, metric, and evaluation code at main 08752a12.