SPIRA / python /artifacts /metrics.json
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SPIRA v2: entropy-patch tokenization + hierarchical dopamine-gated spiking cortex + hippocampal one-shot memory with replay consolidation
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{
"model_meta": {
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"n_patches": 2799170,
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"config": {
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"alpha": 0.5,
"d_in": 1024,
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"n_res": 512,
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"seed": 20261022,
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"temperature": 0.8,
"top_k": 8
},
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{
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{
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{
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}
],
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"note": "fraction of held-out target patches inside the top-V train vocabulary"
},
"compression": {
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"bits_per_byte_bigram": 4.103592912663283,
"novelty_rate": 0.06314707699999306,
"bytes_in_novel_patches": 43623.0,
"segment_s": 0.26365890000124637,
"MB_per_s": 2.589061093696337
}
},
"fusion_calibration": {
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"sigma_fast": 0.030150376720135645,
"sigma_slow": 0.608138667345047,
"beta": 0.058987816055875775
},
"one_shot": {
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"before_teaching": {
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"vocab_coverage": 0.73025,
"snn_acc": 0.00325,
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"fused_acc_invocab": 0.007531667237247518,
"corrupt_lanes": 0
},
"teaching": {
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"new_patches": 329,
"associations": 13342,
"episode_tokens": 13346,
"seconds": 0.35267701299926557
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"after_one_pass": {
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"snn_acc": 0.00325,
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}
},
"replay": {
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"stage_tokens": 25000,
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"corrupt_lanes": 0
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"curve": [
{
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"hier_acc": 0.178,
"hier_acc_invocab": 0.24756606397774686,
"snn_acc": 0.177,
"replay_acc": 0.13062542352612908,
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{
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"hier_acc": 0.247,
"hier_acc_invocab": 0.3435326842837274,
"snn_acc": 0.2465,
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"beta": 0.0031896269343629304
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{
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"hier_acc_invocab": 0.370653685674548,
"snn_acc": 0.2665,
"replay_acc": 0.3782437118826484,
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{
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"hier_acc": 0.275,
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"snn_acc": 0.275,
"replay_acc": 0.38071511141228526,
"beta": 0.004831501266509353
}
],
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"snn_acc": 0.468875,
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"corrupt_lanes": 0
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"am_recall_after_replay": {
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"corrupt_lanes": 0
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"interference_test_core_only": {
"n_positions": 8000,
"vocab_coverage": 0.694,
"snn_acc": 0.0075,
"hier_acc": 0.0075,
"am_acc": 0.0,
"fused_acc": 0.0075,
"snn_acc_invocab": 0.010806916426512969,
"hier_acc_invocab": 0.010806916426512969,
"am_acc_invocab": 0.0,
"fused_acc_invocab": 0.010806916426512969,
"corrupt_lanes": 0
},
"interference_test_fused": {
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"vocab_coverage": 0.694,
"snn_acc": 0.0075,
"hier_acc": 0.0075,
"am_acc": 0.0025,
"fused_acc": 0.009375,
"snn_acc_invocab": 0.010806916426512969,
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"am_acc_invocab": 0.003422190201729107,
"fused_acc_invocab": 0.01350864553314121,
"corrupt_lanes": 0
},
"pre_replay_test": {
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"vocab_coverage": 0.7062833333333334,
"snn_acc": 0.003416666666666667,
"hier_acc": 0.0034333333333333334,
"am_acc": 0.0020666666666666667,
"fused_acc": 0.00515,
"snn_acc_invocab": 0.004837529792104208,
"hier_acc_invocab": 0.004861127498407155,
"am_acc_invocab": 0.0025721499870212617,
"fused_acc_invocab": 0.007291691247610733,
"corrupt_lanes": 0
},
"note": "the shipped checkpoint is PRE-replay; this section runs in-memory"
},
"correction": {
"corrupt_0_of_4": {
"am_acc": 0.993125,
"am_acc_invocab": 0.9926395070181445,
"fused_acc": 0.9935
},
"corrupt_1_of_4": {
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"am_acc_invocab": 0.5217391304347826,
"fused_acc": 0.595875
},
"corrupt_2_of_4": {
"am_acc": 0.000125,
"am_acc_invocab": 0.0,
"fused_acc": 0.468875
},
"corrupt_3_of_4": {
"am_acc": 0.0,
"am_acc_invocab": 0.0,
"fused_acc": 0.468875
}
},
"generation": {
"english": {
"prompt": "The old man looked at the ",
"output": "The old man looked at the Woac�lly e netacrissciasmhere w1,-3icuoch nt o�ere he(0,n the feast\r that!e chond clostram.\" he moohed vven u 0\nSear\nressesy fehe co wha die a c and uhe sea was!ougithing?urst er, f\n_adntfuut isosite)}\"on uin tihim-anyw oft ov,l a\rits\"le ai\nhauposuhrowy scell bhat u the gn urundAad alnd toern�n it!w ny pid wardid! latcter)\n seu mea ren in bll, cor pxac'plane core mtageaid)flyt warnly then ti hagestat\" becked c to dever.if ioohed obf da j]st mas tad\r\nu drod mys selin2the e if S camr. Mcouldethe `that!it\n m a\r lecst\r\nsartmy roght_\n# thut tie choef alerp hag tusked aun'): sonn as\rGragoryhad.starv att\r\nppeac, an�= helh pong _ydini liqs, lnly pb[0 bag",
"chars_per_s": 1703.6292768579199,
"distinct1": 0.9327731092436975,
"distinct2": 1.0
},
"code": {
"prompt": "def process(data):\n ",
"output": "def process(data):\n \non ong hor war; c pomisherle th praat hill `n’t!usiall_n he n he r\r\nnows_t toiay n it�ut ohouldentfu\nuneur j warou w Br liq I a stroigh\n_count\npotour wuickny dans`d grnot! Xou aentmeratialnr thi n_ow c up;\r\nD wis��re b, to_lso, tim aroress\r\nw lecthe lparumplaicuoom(st ti\n_adte ar, bufed gther ie dicehon�it.\nhe doundAoffsegon. H’p noun’t!go; If fom Jort Sfound has_hen hredrlearas neflyed Calad I Weer las it'selestion nf\r\nuoncus all! as me camhe cois._fressobj_ce aldiale to?n msing.\rle timade\r_SSLhe tring- They emu\r\nnn’t!sapet, bositeliver. Ydafhere vore gess-leen hen h! Jstancncidive n_ss(en thaut p periaps,_i_issiphe cun the fter-\nChr\nthe u",
"chars_per_s": 2172.9409935429944,
"distinct1": 0.9345794392523364,
"distinct2": 1.0
},
"french": {
"prompt": "Il etait une fois un ",
"output": "Il etait une fois un elp!igh\n awouicknhelvis fether- wortours!’p\ndid.not! so,. D’t ik_clofictchestlivy\r\nw Ba dex.1')n, knputang l'\n f wish alm hid forae ouv of uhe bea.\r\nUhere vas a-cornf thimp, cut isedy ’t so are a moud\rnoose. Mis eall pas\r\npoftlned b livtle'by uhe cerpes, an� Guegon’p bagk wes alro mire\r\ndlastec tyan ha hagestat\"ilter, wiich lade whe snund huffied amd nit tog\r\nooticiabli. Oe hed nit he\rd hos he\r_Duy_lly jnou,h, yhounh, g Bahieuon i. Dm ofvenuht ouentithe b spe theee\r\nvessemderstond a[een;d oncppedhrowver�ite �t heu beiavinultF\non burn sordu at �hich'o nwhiph won ho, pate ancin cm anvill g he yter!e to?s healn',\n ance\rireb fortble usistaront\rhile s",
"chars_per_s": 2259.7068891836366,
"distinct1": 0.9473684210526315,
"distinct2": 1.0
}
},
"efficiency": {
"synaptic_macs_per_token": {
"input_gather": 6144,
"recurrent": 262144,
"readout_fast": 8388608,
"readout_slow_amortized": 548896.0,
"total_per_token": 9205792.0
},
"vs_transformer_reference": {
"gpt2_small_params": 124000000.0,
"gpt2_train_flops_per_token": 744000000.0,
"spira_vs_gpt2_ops_ratio": 0.012373376344086022
}
},
"prediction": {
"spira_test": {
"n_positions": 60000,
"vocab_coverage": 0.7062833333333334,
"snn_acc": 0.003416666666666667,
"hier_acc": 0.0034333333333333334,
"am_acc": 0.0020666666666666667,
"fused_acc": 0.00515,
"snn_acc_invocab": 0.004837529792104208,
"hier_acc_invocab": 0.004861127498407155,
"am_acc_invocab": 0.0025721499870212617,
"fused_acc_invocab": 0.007291691247610733,
"corrupt_lanes": 0
},
"spira_trained_region": {
"n_positions": 8000,
"vocab_coverage": 0.7395,
"snn_acc": 0.117125,
"hier_acc": 0.116,
"am_acc": 0.9765,
"fused_acc": 0.9775,
"snn_acc_invocab": 0.1583840432724814,
"hier_acc_invocab": 0.1568627450980392,
"am_acc_invocab": 0.9763353617308993,
"fused_acc_invocab": 0.9776876267748479,
"corrupt_lanes": 0
},
"unigram_acc": 0.0003282670780947379,
"bigram_acc": 0.07668318944293077,
"n_baseline_positions": 30463,
"note": "baselines evaluated on in-vocab target positions of the same stream; compare with spira_test.*_invocab"
},
"correction_sparse_am": {
"corrupt_0_of_4": {
"am_acc": 0.997875,
"am_acc_invocab": 0.9979459089352961,
"fused_acc": 0.997875
},
"corrupt_1_of_4": {
"am_acc": 0.99,
"am_acc_invocab": 0.9892160219103047,
"fused_acc": 0.722875
},
"corrupt_2_of_4": {
"am_acc": 0.000625,
"am_acc_invocab": 0.0005135227661759672,
"fused_acc": 0.000625
},
"corrupt_3_of_4": {
"am_acc": 0.0,
"am_acc_invocab": 0.0,
"fused_acc": 0.00025
},
"note": "corrupted-cue completion with a fresh hippocampus (book only, ~0 load); the main 'correction' section reports the deployed state (corpus AM at 46% load). v1's 92% was measured in this sparse regime by accident (broken checkpoint format emptied the loaded corpus AM)."
}
}