Protocol
Self-Supervised Representations and Transfer
Compare self-supervised representations under a limited labeling budget. Distinguish using DINOv2 weights from reproducing its large-scale training.
45–80 active hours60–90 min sessionsAdvanced
Mastery contract
Specialization · Standard 1.0 · Compare self-supervised representations under a limited labeling budget. Distinguish using DINOv2 weights from reproducing its large-scale training.
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Reasoning — not yet passed
The objective states which patches contribute to loss and which information the encoder receives.
Reliable implementation — not yet passed
Probe tests verify frozen weights and training-only preprocessing; checkpoint provenance is recorded.
Reproducible experiment — not yet passed
All transfer comparisons use the same labels and tuning budget; pretrained data uncertainty is disclosed.
Defense and handoff — not yet passed
Defend a representation choice using recorded matched-budget probe/transfer results and a failed transfer case; an embedding visualization alone cannot support the choice.
All four criteria must pass. Activity completion does not satisfy them.
An independent reviewer reruns your work and varies something you did not rehearse: a fresh input, a different working directory, or a declared edge case.
Pilot decisions are provisional, not external credentials. For an appeal or sensitive artifact, contact your designated pilot operator with the submission ID. Export your assessment history.
What you will do
6 total
Derive a masked reconstruction objective and contrast it with a supervised loss; explain why reconstruction quality and transfer quality may disagree.
Implement a small masked-image autoencoder or inspect a pinned official checkpoint; build a frozen-feature linear probe and a matched random-feature baseline.
Compare frozen random, pretrained and fine-tuned features on fixed splits; ablate 2 masking ratios at small scale and report compute.
Debug a supposedly frozen encoder whose weights change and a transfer split that overlaps pretraining identities.
Write a 500–900 word technical report linking the reasoning, code, measurements, and limitations; include the project decision below.
Assess all 4 mastery criteria against saved artifacts, request an independent review, and repeat each failed criterion on a fresh example.
Essentials
A reading session alone never satisfies a mastery criterion.
Store source references, assumptions, and artifact paths beside every result.
Keep an untouched check case that differs from the worked example.
Record all attempts, including failures and results that contradict your prediction.
Use the stated comparison conditions; document every deviation before drawing a conclusion.
Protocol guardrails
Do
- +State the expected result before running the comparison.
- +Keep one minimal reproducible failing case when debugging.
- +Record environment versions and the exact command used.
- +Compare explanations with saved intermediate values.
- +Ask a reviewer to challenge the weakest assumption.
Don't
- ×Do not copy a worked solution and present it as an independent implementation.
- ×Do not tune against held-out evaluation outcomes.
- ×Do not report only the best seed or discard inconvenient runs.
- ×Do not equate elapsed hours or a completed run with a passed assessment.
- ×Do not conceal reduced-scale experiments behind claims about the original full-scale result.
Protocol authorship
Written by NuthinButta as instructional design. The teaching sources are the official references linked in each milestone; the exercises, workload and pass thresholds are ours, not their authors'.