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| author | YurenHao0426 <Blackhao0426@gmail.com> | 2026-08-06 16:54:15 -0500 |
|---|---|---|
| committer | YurenHao0426 <Blackhao0426@gmail.com> | 2026-08-06 16:54:15 -0500 |
| commit | d686f83aa35c2f1d87adfb5705ff02abe1901e9d (patch) | |
| tree | f38642e62c6307d2a7ab6dc25ef8241897f09f3e /results/ep_bias/s0/innovation-cal64-e10-n10k-r0p1-p0p5-s1988.json | |
| parent | 2e2d166f5ee63526fa99bec3a82320c365f76f62 (diff) | |
results: close Rain parameter-bias screen
Diffstat (limited to 'results/ep_bias/s0/innovation-cal64-e10-n10k-r0p1-p0p5-s1988.json')
| -rw-r--r-- | results/ep_bias/s0/innovation-cal64-e10-n10k-r0p1-p0p5-s1988.json | 184 |
1 files changed, 184 insertions, 0 deletions
diff --git a/results/ep_bias/s0/innovation-cal64-e10-n10k-r0p1-p0p5-s1988.json b/results/ep_bias/s0/innovation-cal64-e10-n10k-r0p1-p0p5-s1988.json new file mode 100644 index 0000000..1da2034 --- /dev/null +++ b/results/ep_bias/s0/innovation-cal64-e10-n10k-r0p1-p0p5-s1988.json @@ -0,0 +1,184 @@ +{ + "schema": "rain_ep_structured_bias_screen_v1", + "author": { + "repository": "https://github.com/rain-neuromorphics/energy-based-learning", + "revision": "6b253fd8a5d267535f58ab79992256ef10031ceb" + }, + "protocol": { + "dataset": "FashionMNIST", + "network": "author ConvHopfieldEnergy28 32-64-10", + "algorithm": "positive equilibrium propagation", + "mode": "innovation", + "bias_ratio": 0.1, + "predictor_rate": 0.5, + "neutral_cadence": 1, + "calibration_batches": 64, + "calibration_observations": 64, + "calibration_seconds": 4.21977424621582, + "epochs": 10, + "train_limit": 10000, + "test_limit": 2000, + "batch_size": 128, + "training_iterations": 12, + "inference_iterations": 30, + "seed": 1988, + "device": "cuda", + "autodiff_used_for_learning": false + }, + "metrics": [ + { + "epoch": 1, + "train_accuracy": 0.3568, + "train_cost": 0.40365655641555787, + "test_accuracy": 0.5355, + "test_cost": 0.33721920490264895, + "corrector": { + "step": 78, + "bias_rms": 0.32623520428743413, + "residual_bias_rms": 0.0003058934436845645, + "neutral_observations": 143 + }, + "wall_seconds": 15.673678159713745 + }, + { + "epoch": 2, + "train_accuracy": 0.5438, + "train_cost": 0.325913426733017, + "test_accuracy": 0.569, + "test_cost": 0.3160506935119629, + "corrector": { + "step": 157, + "bias_rms": 0.3278190861390098, + "residual_bias_rms": 0.0006422586917601834, + "neutral_observations": 222 + }, + "wall_seconds": 27.016461849212646 + }, + { + "epoch": 3, + "train_accuracy": 0.5822, + "train_cost": 0.31141259717941283, + "test_accuracy": 0.5555, + "test_cost": 0.3131558494567871, + "corrector": { + "step": 236, + "bias_rms": 0.32959871584392264, + "residual_bias_rms": 0.0026105878059435117, + "neutral_observations": 301 + }, + "wall_seconds": 38.35605311393738 + }, + { + "epoch": 4, + "train_accuracy": 0.5977, + "train_cost": 0.30243987579345705, + "test_accuracy": 0.6235, + "test_cost": 0.29992807960510254, + "corrector": { + "step": 315, + "bias_rms": 0.3255362988399711, + "residual_bias_rms": 0.0008386169230747296, + "neutral_observations": 380 + }, + "wall_seconds": 49.70830178260803 + }, + { + "epoch": 5, + "train_accuracy": 0.6037, + "train_cost": 0.29805392880439757, + "test_accuracy": 0.6205, + "test_cost": 0.2922749881744385, + "corrector": { + "step": 394, + "bias_rms": 0.3270434109858132, + "residual_bias_rms": 0.0003297996560805246, + "neutral_observations": 459 + }, + "wall_seconds": 61.079461336135864 + }, + { + "epoch": 6, + "train_accuracy": 0.6161, + "train_cost": 0.2903678087234497, + "test_accuracy": 0.594, + "test_cost": 0.2984462175369263, + "corrector": { + "step": 473, + "bias_rms": 0.3279944185118071, + "residual_bias_rms": 0.0010317249018418713, + "neutral_observations": 538 + }, + "wall_seconds": 72.47803997993469 + }, + { + "epoch": 7, + "train_accuracy": 0.6268, + "train_cost": 0.28524790496826175, + "test_accuracy": 0.62, + "test_cost": 0.2953354959487915, + "corrector": { + "step": 552, + "bias_rms": 0.32508234497085964, + "residual_bias_rms": 0.000402239431567813, + "neutral_observations": 617 + }, + "wall_seconds": 83.87157440185547 + }, + { + "epoch": 8, + "train_accuracy": 0.6241, + "train_cost": 0.28665888571739195, + "test_accuracy": 0.5865, + "test_cost": 0.30451641178131106, + "corrector": { + "step": 631, + "bias_rms": 0.3215948223491, + "residual_bias_rms": 0.001195856749767784, + "neutral_observations": 696 + }, + "wall_seconds": 95.33216047286987 + }, + { + "epoch": 9, + "train_accuracy": 0.6231, + "train_cost": 0.28508677973747254, + "test_accuracy": 0.6315, + "test_cost": 0.27816396999359133, + "corrector": { + "step": 710, + "bias_rms": 0.3183335932172959, + "residual_bias_rms": 0.002652679784133837, + "neutral_observations": 775 + }, + "wall_seconds": 106.76524424552917 + }, + { + "epoch": 10, + "train_accuracy": 0.6377, + "train_cost": 0.2754653572559357, + "test_accuracy": 0.5595, + "test_cost": 0.3280595178604126, + "corrector": { + "step": 789, + "bias_rms": 0.32612410406317766, + "residual_bias_rms": 0.0003998780642494185, + "neutral_observations": 854 + }, + "wall_seconds": 118.15158224105835 + } + ], + "final": { + "epoch": 10, + "train_accuracy": 0.6377, + "train_cost": 0.2754653572559357, + "test_accuracy": 0.5595, + "test_cost": 0.3280595178604126, + "corrector": { + "step": 789, + "bias_rms": 0.32612410406317766, + "residual_bias_rms": 0.0003998780642494185, + "neutral_observations": 854 + }, + "wall_seconds": 118.15158224105835 + } +} |
