| { |
| "declared_utc": "2026-10-04T14:15:01.268646+00:00", |
| "protocol": { |
| "adapter": { |
| "files": { |
| "TRAINING_COMPLETE.json": "e64a09145b2974e70ca164702b1b9dd3c275257443f7f690202d1b4c3a0291e7", |
| "adapter_config.json": "0d3a2dc622ee11b6309c4f9d0cc99bac9d181f0557e215a0dd263bad2b3810b1", |
| "adapter_model.safetensors": "7412c96c3018cb86e63e755e11125535b0f0c6c3d21e7d0ac625845996bd8922", |
| "added_tokens.json": "a32bc0d990603eb93fd389dc164fe6fbfc442db2ab3a65e4a99a249433ab11f6", |
| "run_manifest.json": "4a262a354b2b9b036bc743d9ca2f28384c8c20c510ddbaccb6033f957437898b", |
| "special_tokens_map.json": "bd1a530e68d3e09aa7a45be45eff6f3f6930f6111d227ac57fb75073adf954ec", |
| "tokenizer.json": "fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a", |
| "tokenizer_config.json": "2bcc8b527e0f7b3f5ceb74e13708b004316aa970972a1399b199c6b5f9cd243e", |
| "vocab.json": "ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910" |
| }, |
| "path": "/persistent-drive/VibeGame-8B/runs/teacher-v2/adapter", |
| "sha256": "1ee9c6587d1addacb07677442b2adb26432d394efa959c92152f8a8b63637113" |
| }, |
| "base_model": "unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit", |
| "base_quantization": "unchanged pinned 4-bit base", |
| "base_revision": "4858886f896bd05db823557fc5cbc4ac28342af7", |
| "batch_size": 8, |
| "budget_policy": { |
| "balance_reserve_fraction": 0.1, |
| "generation_margin": 1.5, |
| "limitations": "Conservative estimate, not a guaranteed upper bound or a billing cap; throughput, import time and Colab rates can vary.", |
| "overlap_credit": false, |
| "setup_seconds": 1800, |
| "validation_seconds_per_prompt": 90 |
| }, |
| "decoding": { |
| "seed": 42, |
| "temperature": 0 |
| }, |
| "dtype": "float16", |
| "expected_count": 500, |
| "experiment": "evaluation-a100-v1", |
| "godot_sha256": "db07cae7de644278a1884d4552bdf2bca3f5d30131b18faf3a0c4d730080b199", |
| "gpu_runtime": { |
| "cuda_available": true, |
| "cuda_version": "13.0", |
| "device_count": 1, |
| "gpu": "NVIDIA A100-SXM4-40GB", |
| "packages": { |
| "bitsandbytes": "0.50.2", |
| "peft": "0.21.0", |
| "transformers": "4.56.2", |
| "unsloth": "2026.9.14" |
| }, |
| "torch_version": "2.11.0+cu130" |
| }, |
| "hardware_tier": "Colab Pro A100; training previously completed on a free T4", |
| "max_new_tokens": 3072, |
| "prompts_sha256": "1afaf25c274d6b8490321ad9a57323cf6a5c1e48c01a1e5d651ae8525b7cd1ff", |
| "rationale": "Predeclared separate full A100 pass to reduce completion time after the free T4 quota was exhausted. The completed adapter and decoding are unchanged. The A100 500-prompt pass is the primary final protocol; the partial T4 run remains separate and will be disclosed. No prompt-level results are pooled or selected between runs. Capacity decisions use only admitted training prompts.", |
| "run_seconds": 60, |
| "sample_indices": [ |
| 0, |
| 200, |
| 400 |
| ], |
| "schema_version": 1, |
| "source_sha256": { |
| "benchmark_batch.py": "40de0acb473112f01fa5607a35b1a1dd7d50580e22b1cc04bd58d82b184a1429", |
| "evaluate.py": "4db2d4594a0e254a21031db1d7947ad232e0437b44ababed7545d45be80d2168", |
| "evaluate_pro.py": "c9b911d659ce184301688336fec584c94e1defd97f17c3db585e72016900073e", |
| "generate.py": "f1ea62d283f78a301248eb6a8c1cba6088f72fc4cdb1adea53ef4145ddb5d900" |
| }, |
| "source_t4_directory": "/persistent-drive/VibeGame-8B/runs/teacher-v2/evaluation", |
| "source_t4_manifest_sha256": "b95588cb3da864431f0059342d04c2b15cf489493bd7d021ba9f2cc37096d6d8", |
| "system_prompt_sha256": "184cc6be584c2181933c72eaf1e683459b4f3d37a8a5c9208692f509d9f3a2ef", |
| "t4_evidence_policy": "Read only; preserve every result and interrupted attempt; never pool scores", |
| "train_sha256": "bb64ec6ce57883589da7239a36bf07a2eea64b4d73ff002363d75e5c24a4582a", |
| "workers": 4 |
| } |
| } |
|
|
