Download evaluation/training_protocol.json from eac123/ultrafauna: direct link, hf CLI and curl.
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https://huggingface.co/eac123/ultrafauna/resolve/main/evaluation/training_protocol.json
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hf download hf://eac123/ultrafauna/evaluation/training_protocol.json
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curl -L -o training_protocol.json https://huggingface.co/eac123/ultrafauna/resolve/main/evaluation/training_protocol.json
4.19 kB
| { | |
| "version": "local_joint_precision_v1", | |
| "seed": 1729, | |
| "steps": 4000, | |
| "lr": 0.0001, | |
| "weight_decay": 0.01, | |
| "validation_interval": 500, | |
| "initialization": { | |
| "sha256": "0834dba67b83c7ccc1b26f3c8a964d1573fda410ebe0ea0a7cb545e756a13b8a", | |
| "width": 64 | |
| }, | |
| "architecture": "Unchanged single local bat/rodent CNN; all parameters trainable, no scene veto or external model.", | |
| "objective": "Per-example/group/polarity balanced local loss; BAT negatives weighted2;75% worst2% time-cell negative loss; +.25 same-location identity margin; weak TRAIN field recording MIL every second update weight.25. Identity margin disabled for synthetic co-occurrence.", | |
| "sampling": "Three annotated bat contexts;two bounded noise contexts;three captive rodent contexts;three whole field noise contexts;one additional captive hard negative;one digital-silence control. Negative pools half parent-balanced hard mining and half parent-balanced uniform. No rank from held audio.", | |
| "augmentation": "Same TRAIN gain -24..+12dB and continuous-tone augmentation as prior run;25% bat/rodent mixtures with conservative negative-mask intersection. One weak positive complete5sec bag every other step; no annotation/pseudo-model selects its witness.", | |
| "optimizer": "AdamW100step warmup/cosine to10%;gradient norm5;EMA .99;fresh optimizer", | |
| "selection": "Mean VAL focal-bat recall and whole-recording bat recall at lowest cut satisfying <=5% observed FPR separately on VAL reviewed-noise regions,captive-rodent contexts,and whole reviewed background recordings. VAL temporary cut selects weights only, never exported. Earliest tie, original base included as eligible fallback.", | |
| "calibration": "After weight selection, lowest float32 BAT threshold with <=5% observed FPR in EACH corresponding CAL negative bucket. No recall guarantee; report achieved positive retention. Rodent threshold highest retaining90% CAL focal rodent regions, diagnostic only; one captive CAL parent.", | |
| "controls": "Apply identical new CAL rule to unchanged base weights, alongside original base rule. Separates threshold-only changes from training. Never choose rule or checkpoint from transfer/private outcomes.", | |
| "evaluation": "Known transfer cohorts were scored after freezing weights and calibration; not an untouched final test.", | |
| "forbidden_training_calibration": [ | |
| "Held-out evaluation recordings", | |
| "Calibration/validation used only for their assigned roles", | |
| "Private user recordings" | |
| ], | |
| "data_scope": "Reuse corrected base roles. Extra captive peak crops from existing hard-negative TRAIN rows only: BAT-negative context, no invented rodent-positive label. All weak human-verified TRAIN positive recordings supply MIL, not dense targets. No source held role is promoted.", | |
| "limitations": [ | |
| "No new pup training collection is added. Existing pup VAL/test cannot be moved into training.", | |
| "The5% budget is an observed CAL fraction, not a guaranteed deployment FPR. Background calibration exposure is short.", | |
| "No fresh device-held final cohort; report history and sample counts." | |
| ], | |
| "code_sha256": { | |
| "local_joint_precision.py": "b9cf262a87af507b98323083344c95b24ca1fe43b90fb70ffd6f366fbe5e83fc", | |
| "prepare_local_joint_precision.py": "56ddcb289333947567deca2bd3f9afad9ac28c52a196482b9fe5f26cc8d90976", | |
| "train_local_joint_precision.py": "22357a7b6eba08ff93faa89ec6fdf31afee0e3cb211dea53ff2b2c9dfd7ea313", | |
| "local_joint_field_model.py": "2523b722b38f83fab5e99cd8a23787508e76c407ac53b3c6a8cfda88ec9915db", | |
| "train_local_joint_field_refined.py": "f5516ce28ea7e2586249ede0436dd7036dce5c08b0d138530ada8bfe6f439841" | |
| }, | |
| "pre_gradient_amendment": { | |
| "previous_protocol_sha256": "55bd8a4bcd2533dbc221d11c2c4f0431fe4158219e58a5c3472cb04e0c63260b", | |
| "reason": "Auxiliary identity contrast requires explicit opposite-class absence; unknown labels must not acquire negative supervision.", | |
| "weights_fitted_so_far": 0, | |
| "mining_reused_sha256": "ea60e1f3ca5da41589487d3e525c2d94886206107532056408fd65ed1ff493ab" | |
| }, | |
| "public_redaction": "Absolute paths and source identifiers omitted. Original frozen protocol SHA256 is recorded in calibration.json." | |
| } | |