| { |
| "config": { |
| "epochs": 1, |
| "seed": 1, |
| "lr": 2e-05, |
| "lora": 16, |
| "accum": 4, |
| "batch": 2, |
| "perm_kl": 0.0, |
| "perm_frac": 0.3, |
| "ord_w": 0.0, |
| "p_none": 0.1, |
| "p_none_distract": 0.12, |
| "p_distract": 0.15, |
| "p_none_pair": 0.25, |
| "synthetic_repeat": 1, |
| "public_frac": 1.0, |
| "head_lr": 0.0, |
| "weight_decay": 0.01, |
| "anchor_w": 0.0, |
| "label_smoothing": 0.0, |
| "brier_w": 0.0, |
| "focal_gamma": 0.0, |
| "dtype": "bf16", |
| "checkpointing": 1, |
| "max_state": 7552, |
| "base": "Qwen/Qwen3.5-4B-Base", |
| "base_revision": "1001bb4d826a52d1f399e183466143f4da7b741b", |
| "init_from": "jaredpalmer/kev-4b@957b91e762e883935830246eeb02381f9d2694b6", |
| "data": "evals/round10/skills/train.jsonl", |
| "replay": 4000 |
| }, |
| "config_sha256": "08aa7634eef0409340edd9df72b4b347bdda02e87b25c920e205dc727911525d", |
| "suite_sha256": "a8f50e481b7d90b97da049e0ff6a01cee2f1ed204aed61a8265af0edbb5514d2", |
| "source_hashes": { |
| "kev/__init__.py": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", |
| "kev/anchors.py": "6963eafdb276db5a6c94d939eae675c761555553b8d0f963ffd803448beaabbb", |
| "kev/api.py": "7bffacfb762c626b8bc2f670f350295af5ccb0883dbe90239c7d2f8e5ef56582", |
| "kev/autoresearch.py": "f7d7fabb9c0df7065bee3fec4aa4bee7028c5d1565847aefe2d74e3d7d40ed8a", |
| "kev/benchmark.py": "10a892d76cb4c200e94d0a68ee74054aa1870d7f484c0530a531cacfa75032ed", |
| "kev/calibrate.py": "c1eff4744fabd349e8abca86777a7aa0cbea44904c8223d3b61fca3d43741519", |
| "kev/checkpoint.py": "f3edb4d159c0aa12d7006fc599fe6ebc3f2c288b3b69890c289f7dac451dd03d", |
| "kev/compare.py": "3606dbf98bb305d66420158498cb837304d2edb8dab01cdaf2ec42964bef3435", |
| "kev/composition.py": "f335ed17e18e0a544893db5e22b9a059e6ce1b2e14dbb863ac7d7bbf8f3e0536", |
| "kev/contrastive.py": "cbb979aa5d40265ad0e64695f94b281d91751fa405811ddfa8212fede111edcf", |
| "kev/cuda_graphs.py": "12f1953fea8f77c3c9dff29468202fbb37545145f93d3618194565a89949fd55", |
| "kev/data.py": "e77a2fffeb8ee7e05b118893be8e38b8358aef97c3ca2e143cdce208201b92f9", |
| "kev/device.py": "d1677fd98ec0979c7284546306e34e0d09298ca4042fc39eb2b32a74f4e975c4", |
| "kev/evaluate.py": "999264f2837dcfbf2ec93601aa4745e701698ab850a43ad89324672a6604965c", |
| "kev/experiment.py": "644adedf43fbd10566830fa6094e16dd001b8cad29d9b9da82f0e0f245ca06b1", |
| "kev/jev.py": "acd4cc3f1844e438cc83a8d409c15ef78a5ef64d39ea10f583d75a6c7646b243", |
| "kev/metrics.py": "dba8d90550999edcd642581fb4da0367bd4b39d08471815184fa732d11e137b9", |
| "kev/mlx_model.py": "f582428796faf6bf962b772a69a6227ac3259ccbd3215c0c8b55ce28dbbd0909", |
| "kev/model.py": "2634ffe7747d69473fb6596942c248e5df2586df3610bd1adb47e7e9acd99f96", |
| "kev/plot.py": "0874bcff2885d8155a1cceade0de8a275a7163d3c3fd6aa0c294e8ccf5ff7e02", |
| "kev/predictors.py": "4d02906c285d78bcbd91908f4fc86577ccc95c320d704817f6444aabbc4fcd4f", |
| "kev/publish.py": "8abc9bcf4a01365697b05cf3c5ad0013462bd92d005f5616954e40ab1100c7aa", |
| "kev/serve.py": "57d379bbcdeb3e4d4c3fdde5471e4dddeaf7710b8ed61ecad3466f3b67e6c610", |
| "kev/study_v3.py": "7891150aa623e4479c7c789d4dc4662f186132b37b7bac1e1f072b9e08ee13e3", |
| "kev/suite.py": "32b2882d1ea0fe5d03ba4d676a6180d580545f157e36fa715e7e89169ec99130", |
| "kev/train.py": "68428ed43b3e362e52d4650dc5296ab88767061f7998a525715e1b306eeef474", |
| "kev/transfer_v9.py": "0902409742151250a28af1fd8f42258b70fcc161f3deed3ee35fe3f473f3c763", |
| "modal_app.py": "7c6bc859f7d3e7011539a8f5e9e90390288cc72b5d80f911c8841c068f4d1136", |
| "pyproject.toml": "7c17fbe9efcadda3eb488b59adf1b6db5938cd33af4d3bd389ce4359b73fcc7d", |
| "uv.lock": "a9922dbb89acdef78299fd2b4a8c3f7f0fa1b2bc08b55595b6926fa785a9c466" |
| }, |
| "git_commit": "6d02f5d066cd34958dfd15ffa5d2f6f0f4c21a63", |
| "platform": "Linux-4.19.0-gvisor-x86_64-with-glibc2.36", |
| "torch": "2.8.0+cu128", |
| "device": "cuda", |
| "gpu": "NVIDIA H200", |
| "legacy_checkpoint": false, |
| "measured_checkpoint": { |
| "requested": "/runs/r10-skills/00-trial-0/checkpoint", |
| "resolved": "/runs/r10-skills/00-trial-0/checkpoint", |
| "head_sha256": "979aaa60135274973a6dc57fe24dfc4f1ce88e65df46c73d86b2047c94d897df", |
| "adapter_sha256": "90e817356246e7f18bfa7ca3d31794cd4fbeb3332a66a84cb51d9ceae925f2b2", |
| "inference_temperature": 1.0 |
| } |
| } |
|
|
