| { |
| "kind": "exact_authored_source_audit", |
| "source": "source/authored/sections/experiments.tex", |
| "source_sha256": "fcd88332cbe90aff62337c3add333f71fc542736b3e459015a28f0b08ae3c55b", |
| "table_heading_line": 26, |
| "caption_line": 42, |
| "table_rows": [ |
| { |
| "parameters_approx": 1000.0, |
| "pure_tf": 0.056, |
| "pure_ssm": 0.084, |
| "tf_to_ssm": 0.1, |
| "ssm_to_tf": 0.087 |
| }, |
| { |
| "parameters_approx": 2000.0, |
| "pure_tf": 0.352, |
| "pure_ssm": 0.305, |
| "tf_to_ssm": 0.433, |
| "ssm_to_tf": 0.999 |
| }, |
| { |
| "parameters_approx": 6000.0, |
| "pure_tf": 0.727, |
| "pure_ssm": 0.485, |
| "tf_to_ssm": 0.822, |
| "ssm_to_tf": 1.0 |
| }, |
| { |
| "parameters_approx": 12000.0, |
| "pure_tf": 0.923, |
| "pure_ssm": 0.931, |
| "tf_to_ssm": 0.908, |
| "ssm_to_tf": 1.0 |
| } |
| ], |
| "literal_table_comparison": { |
| "hybrid_ssm_to_tf_at_approximately_2000": 0.999, |
| "pure_tf_at_approximately_12000": 0.923, |
| "pure_ssm_at_approximately_12000": 0.931, |
| "parameter_ratio_12000_over_2000": 6.0, |
| "strict_table_value_is_exactly_one": false |
| }, |
| "source_caption_says_perfect": true, |
| "source_results_says_roughly_six_times": true, |
| "assessment": "The authored table supports the approximate 6x/near-perfect comparison (.999 versus .923/.931), but its printed .999 is not literally 1.000 while the caption calls it perfect. This is source evidence, not an independent learned-model reproduction.", |
| "training_route": { |
| "official_train_file": "source/official-code/micro_hf/train_utils.py", |
| "official_train_file_sha256": "ec4ccc0fa03f636f141904484f54763576e741c6f3586b1405343bb844c7c040", |
| "hard_coded_cuda_calls": 1, |
| "torch_cuda_available_on_this_host": false, |
| "result_artifacts_present": false, |
| "reason_no_local_training_rerun": "The official micro_hf entry point hard-codes CUDA tensors; this host has no CUDA device. The checkout contains figures and lrs.json metadata but no per-run evaluation JSON/CSV/checkpoint results." |
| } |
| } |
|
|
