diff --git a/examples/autodecoder.jl b/examples/autodecoder.jl index 81eac1db..b4a4dc4d 100644 --- a/examples/autodecoder.jl +++ b/examples/autodecoder.jl @@ -191,7 +191,7 @@ function train_SNF( NN = AutoDecoder(decoder, metadata._Ns, l; init_weight = init_code) _batchsize = isnothing(_batchsize) ? numobs(_data) ÷ 100 : _batchsize - batchsize_ = isnothing(batchsize_) ? numobs(_data) : batchsize_ + batchsize_ = isnothing(batchsize_) ? numobs(_data) ÷ 1 : batchsize_ lossfun = regularize_autodecoder(mse; σ2inv, α, λ1, λ2) @@ -201,18 +201,19 @@ function train_SNF( lrs = (1f-3, 5f-4, 2f-4, 1f-4, 5f-5, 2f-5, 1f-5,) Nlrs = length(lrs) - weightdecay = if isnothing(WeightDecayOpt) | (WeightDecayOpt === DecoderWeightDecay) - ca_axes = p_axes(NN; rng) - DecoderWeightDecay(0f0, ca_axes) - elseif WeightDecayOpt === IdxWeightDecay - decoder_idx = if isnothing(weight_decay_ifunc) | (weight_decay_ifunc === decoder_indices) - # decoder_W_indices(NN; rng) # WD on decoder weights - decoder_indices(NN; rng) # WD on decoder weights and biases + weightdecay = if isnothing(WeightDecayOpt) | (WeightDecayOpt === IdxWeightDecay) + + decoder_idx = if isnothing(weight_decay_ifunc) | (weight_decay_ifunc === decoder_W_indices) + decoder_W_indices(NN; rng) # WD on decoder weights and biases else weight_decay_ifunc(NN; rng) end IdxWeightDecay(0f0, decoder_idx) + + elseif WeightDecayOpt === DecoderWeightDecay + ca_axes = p_axes(NN; rng) + DecoderWeightDecay(0f0, ca_axes) else error("Unsupported weight decay algorithm") end @@ -864,7 +865,7 @@ function eval_model( model::NeuralEmbeddingModel, x::Tuple, p::AbstractArray; - batchsize = numobs(x) ÷ 101, + batchsize = numobs(x) ÷ 100, device = Lux.cpu_device(), ) loader = MLUtils.DataLoader(x; batchsize, shuffle = false, partial = true) diff --git a/examples/burgers_fourier1D/autodecode.jl b/examples/burgers_fourier1D/autodecode.jl index a20ddb56..f3dc5aed 100644 --- a/examples/burgers_fourier1D/autodecode.jl +++ b/examples/burgers_fourier1D/autodecode.jl @@ -1,8 +1,4 @@ # -""" -Train an autoencoder on 1D Burgers data -""" - using GeometryLearning include(joinpath(pkgdir(GeometryLearning), "examples", "autodecoder.jl")) #======================================================# @@ -10,43 +6,47 @@ include(joinpath(pkgdir(GeometryLearning), "examples", "autodecoder.jl")) rng = Random.default_rng() Random.seed!(rng, 460) +prob = BurgersViscous1D(1f-4) device = Lux.gpu_device() datafile = joinpath(@__DIR__, "burg_visc_re10k", "data.jld2") - modeldir = joinpath(@__DIR__, "dump") modelfile = joinpath(modeldir, "model_08.jld2") -prob = BurgersViscous1D(1f-4) - E = 3500 # epochs l = 8 # latent h = 5 # num hidden w = 128 # width -λ1, λ2 = 0f0, 0f0 # L1 / L2 reg -σ2inv, α = 1f-2, 0f-0 # code / Lipschitz regularization -weight_decays = 5f-2 # AdamW weight decay +λ1, λ2 = 0f0, 0f0 +σ2inv, α = 1f-1, 0f-0 # 1f-1, 1f-3 +weight_decays = 1f-2 # 1f-2 +WeightDecayOpt = IdxWeightDecay +weight_decay_ifunc = decoder_W_indices -_Ib, Ib_ = [2], [2] -Ix = LinRange(1, 8192, 1024) .|> Base.Fix1(round, Int) -makedata_kws = (; Ix, _Ib, Ib_, _It = :, It_ = :) +_Ib, Ib_ = [5,], [5,] # 1, 2 work +Ix = LinRange(1, 8192, 1024) .|> Base.Fix1(round, Int) +_It = Colon() # LinRange(1, 1000, 200 ) .|> Base.Fix1(round, Int) +makedata_kws = (; Ix, _Ib, Ib_, _It = _It, It_ = :) ## train -# isdir(modeldir) && rm(modeldir, recursive = true) -# train_SNF(datafile, modeldir, l, h, w, E; -# rng, warmup = true, -# λ1, λ2, σ2inv, α, weight_decays, device, makedata_kws, -# ) +isdir(modeldir) && rm(modeldir, recursive = true) +train_SNF(datafile, modeldir, l, h, w, E; + rng, warmup = true, makedata_kws, + λ1, λ2, σ2inv, α, weight_decays, device, + WeightDecayOpt, weight_decay_ifunc, +) -## process outdir = joinpath(modeldir, "results") postprocess_SNF(prob, datafile, modelfile, outdir; rng, device, makeplot = true, verbose = true) -x, t, ud, up, _ = evolve_SNF(prob, datafile, modelfile, _Ib[1]; rng, device, verbose = true) +x, t, ud, up, _ = evolve_SNF(prob, datafile, modelfile, Ib_[1]; rng, device, verbose = true) plt = plot(x[1,:], ud[1,:,begin], w = 4, c = :black, label = nothing) plot!(plt, x[1,:], ud[1,:,end ], w = 4, c = :black, label = "data") plot!(plt, x[1,:], up[1,:,end ], w = 4, c = :red , label = "pred") display(plt) + +@show sqrt(mse(up, ud) / mse(ud, 0 * ud)) +@show norm(up - ud, Inf) / sqrt(mse(ud, 0 * ud)) #======================================================# nothing diff --git a/examples/burgers_fourier1D/autodecode1.jl b/examples/burgers_fourier1D/autodecode1.jl new file mode 100644 index 00000000..bcae9334 --- /dev/null +++ b/examples/burgers_fourier1D/autodecode1.jl @@ -0,0 +1,51 @@ +# +using GeometryLearning +include(joinpath(pkgdir(GeometryLearning), "examples", "autodecoder.jl")) +#======================================================# + +rng = Random.default_rng() +Random.seed!(rng, 460) + +prob = BurgersViscous1D(1f-4) +device = Lux.gpu_device() +datafile = joinpath(@__DIR__, "burg_visc_re10k", "data.jld2") +modeldir = joinpath(@__DIR__, "dump1") +modelfile = joinpath(modeldir, "model_08.jld2") + +E = 3500 # epochs +l = 8 # latent +h = 5 # num hidden +w = 128 # width + +λ1, λ2 = 0f0, 0f0 +σ2inv, α = 1f-1, 0f-0 # 1f-1, 1f-3 +weight_decays = 1f-2 # 1f-2 +WeightDecayOpt = IdxWeightDecay +weight_decay_ifunc = decoder_indices + +_Ib, Ib_ = [5,], [5,] # 1, 2, 3 work +Ix = Colon() # LinRange(1, 8192, 1024) .|> Base.Fix1(round, Int) +_It = Colon() # LinRange(1, 1000, 200 ) .|> Base.Fix1(round, Int) +makedata_kws = (; Ix, _Ib, Ib_, _It = _It, It_ = :) + +## train +isdir(modeldir) && rm(modeldir, recursive = true) +train_SNF(datafile, modeldir, l, h, w, E; + rng, warmup = true, makedata_kws, + λ1, λ2, σ2inv, α, weight_decays, device, + WeightDecayOpt, weight_decay_ifunc, +) + +outdir = joinpath(modeldir, "results") +postprocess_SNF(prob, datafile, modelfile, outdir; rng, device, + makeplot = true, verbose = true) +x, t, ud, up, _ = evolve_SNF(prob, datafile, modelfile, Ib_[1]; rng, device, verbose = true) +plt = plot(x[1,:], ud[1,:,begin], w = 4, c = :black, label = nothing) +plot!(plt, x[1,:], ud[1,:,end ], w = 4, c = :black, label = "data") +plot!(plt, x[1,:], up[1,:,end ], w = 4, c = :red , label = "pred") +display(plt) + +@show sqrt(mse(up, ud) / mse(ud, 0 * ud)) +@show norm(up - ud, Inf) / sqrt(mse(ud, 0 * ud)) +#======================================================# +nothing diff --git a/examples/burgers_fourier1D/data_burg1d/README b/examples/burgers_fourier1D/data_burg1d/README new file mode 100644 index 00000000..63dded6b --- /dev/null +++ b/examples/burgers_fourier1D/data_burg1d/README @@ -0,0 +1 @@ +mu = (0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2) diff --git a/examples/burgers_fourier1D/burg_visc_re10k/traj_1.gif b/examples/burgers_fourier1D/data_burg1d/traj_1.gif similarity index 100% rename from examples/burgers_fourier1D/burg_visc_re10k/traj_1.gif rename to examples/burgers_fourier1D/data_burg1d/traj_1.gif diff --git a/examples/burgers_fourier1D/burg_visc_re10k/traj_2.gif b/examples/burgers_fourier1D/data_burg1d/traj_2.gif similarity index 100% rename from examples/burgers_fourier1D/burg_visc_re10k/traj_2.gif rename to examples/burgers_fourier1D/data_burg1d/traj_2.gif diff --git a/examples/burgers_fourier1D/burg_visc_re10k/traj_3.gif b/examples/burgers_fourier1D/data_burg1d/traj_3.gif similarity index 100% rename from examples/burgers_fourier1D/burg_visc_re10k/traj_3.gif rename to examples/burgers_fourier1D/data_burg1d/traj_3.gif diff --git a/examples/burgers_fourier1D/burg_visc_re10k/traj_4.gif b/examples/burgers_fourier1D/data_burg1d/traj_4.gif similarity index 100% rename from examples/burgers_fourier1D/burg_visc_re10k/traj_4.gif rename to examples/burgers_fourier1D/data_burg1d/traj_4.gif diff --git a/examples/burgers_fourier1D/burg_visc_re10k/traj_5.gif b/examples/burgers_fourier1D/data_burg1d/traj_5.gif similarity index 100% rename from examples/burgers_fourier1D/burg_visc_re10k/traj_5.gif 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a/examples/burgers_fourier1D/dump/results/dudx4_667_FWD_AD.png b/examples/burgers_fourier1D/dump/results/dudx4_667_FWD_AD.png deleted file mode 100644 index c618001c..00000000 Binary files a/examples/burgers_fourier1D/dump/results/dudx4_667_FWD_AD.png and /dev/null differ diff --git a/examples/burgers_fourier1D/dump/results/train_u1_k1.png b/examples/burgers_fourier1D/dump/results/train_u1_k1.png deleted file mode 100644 index 22c4fc23..00000000 Binary files a/examples/burgers_fourier1D/dump/results/train_u1_k1.png and /dev/null differ diff --git a/examples/burgers_fourier1D/dump/statistics_01.txt b/examples/burgers_fourier1D/dump/statistics_01.txt deleted file mode 100644 index 7867461f..00000000 --- a/examples/burgers_fourier1D/dump/statistics_01.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 0.043753617 || TEST LOSS: 0.04375362 -#======================# -TRAIN STATS -R² score: 0.8945793 -MSE (mean SQR error): 0.04240581 -RMSE (Root MSE): 0.20592672 -MAE (mean ABS error): 0.11898308 -maxAE (max ABS error) 1.1165816 -Lipschitz bound: 5822.465 - -#======================# -#======================# -TEST STATS -R² score: 0.8945793 -MSE (mean SQR error): 0.04240581 -RMSE (Root MSE): 0.20592672 -MAE (mean ABS error): 0.11898308 -maxAE (max ABS error) 1.1165816 -Lipschitz bound: 5822.465 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_02.txt b/examples/burgers_fourier1D/dump/statistics_02.txt deleted file mode 100644 index 269e1501..00000000 --- a/examples/burgers_fourier1D/dump/statistics_02.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 0.00013969521 || TEST LOSS: 0.00013969521 -#======================# -TRAIN STATS -R² score: 0.9999037 -MSE (mean SQR error): 5.4943976e-5 -RMSE (Root MSE): 0.0074124206 -MAE (mean ABS error): 0.0028252765 -maxAE (max ABS error) 0.8498828 -Lipschitz bound: 7.441357e6 - -#======================# -#======================# -TEST STATS -R² score: 0.9999037 -MSE (mean SQR error): 5.4943972e-5 -RMSE (Root MSE): 0.00741242 -MAE (mean ABS error): 0.0028252762 -maxAE (max ABS error) 0.8498828 -Lipschitz bound: 7.441357e6 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_03.txt b/examples/burgers_fourier1D/dump/statistics_03.txt deleted file mode 100644 index eff38ef6..00000000 --- a/examples/burgers_fourier1D/dump/statistics_03.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 7.488184e-5 || TEST LOSS: 7.488184e-5 -#======================# -TRAIN STATS -R² score: 0.99997014 -MSE (mean SQR error): 1.7008668e-5 -RMSE (Root MSE): 0.0041241567 -MAE (mean ABS error): 0.0014307484 -maxAE (max ABS error) 0.7210185 -Lipschitz bound: 6.918215e6 - -#======================# -#======================# -TEST STATS -R² score: 0.99997014 -MSE (mean SQR error): 1.700867e-5 -RMSE (Root MSE): 0.0041241567 -MAE (mean ABS error): 0.0014307483 -maxAE (max ABS error) 0.7210185 -Lipschitz bound: 6.918215e6 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_04.txt b/examples/burgers_fourier1D/dump/statistics_04.txt deleted file mode 100644 index fbed7ee3..00000000 --- a/examples/burgers_fourier1D/dump/statistics_04.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 2.863764e-5 || TEST LOSS: 2.863764e-5 -#======================# -TRAIN STATS -R² score: 0.9999923 -MSE (mean SQR error): 4.3907253e-6 -RMSE (Root MSE): 0.0020954057 -MAE (mean ABS error): 0.0008059722 -maxAE (max ABS error) 0.25440952 -Lipschitz bound: 9.224318e6 - -#======================# -#======================# -TEST STATS -R² score: 0.9999923 -MSE (mean SQR error): 4.3907257e-6 -RMSE (Root MSE): 0.002095406 -MAE (mean ABS error): 0.00080597226 -maxAE (max ABS error) 0.25440952 -Lipschitz bound: 9.224318e6 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_05.txt b/examples/burgers_fourier1D/dump/statistics_05.txt deleted file mode 100644 index a76b429d..00000000 --- a/examples/burgers_fourier1D/dump/statistics_05.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 1.5624597e-5 || TEST LOSS: 1.5624597e-5 -#======================# -TRAIN STATS -R² score: 0.99999535 -MSE (mean SQR error): 2.651078e-6 -RMSE (Root MSE): 0.0016282131 -MAE (mean ABS error): 0.00060143234 -maxAE (max ABS error) 0.2321093 -Lipschitz bound: 1.2521752e7 - -#======================# -#======================# -TEST STATS -R² score: 0.99999535 -MSE (mean SQR error): 2.651078e-6 -RMSE (Root MSE): 0.0016282131 -MAE (mean ABS error): 0.00060143234 -maxAE (max ABS error) 0.2321093 -Lipschitz bound: 1.2521752e7 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_06.txt b/examples/burgers_fourier1D/dump/statistics_06.txt deleted file mode 100644 index d5cfc454..00000000 --- a/examples/burgers_fourier1D/dump/statistics_06.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 1.0309801e-5 || TEST LOSS: 1.0309801e-5 -#======================# -TRAIN STATS -R² score: 0.9999979 -MSE (mean SQR error): 1.1817948e-6 -RMSE (Root MSE): 0.0010871039 -MAE (mean ABS error): 0.0004936915 -maxAE (max ABS error) 0.13794763 -Lipschitz bound: 1.5095981e7 - -#======================# -#======================# -TEST STATS -R² score: 0.9999979 -MSE (mean SQR error): 1.1817948e-6 -RMSE (Root MSE): 0.0010871039 -MAE (mean ABS error): 0.0004936915 -maxAE (max ABS error) 0.13794763 -Lipschitz bound: 1.5095981e7 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_07.txt b/examples/burgers_fourier1D/dump/statistics_07.txt deleted file mode 100644 index 37e59c47..00000000 --- a/examples/burgers_fourier1D/dump/statistics_07.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 7.5263065e-6 || TEST LOSS: 7.526305e-6 -#======================# -TRAIN STATS -R² score: 0.99999875 -MSE (mean SQR error): 7.043928e-7 -RMSE (Root MSE): 0.0008392811 -MAE (mean ABS error): 0.00037126476 -maxAE (max ABS error) 0.10817945 -Lipschitz bound: 1.8704468e7 - -#======================# -#======================# -TEST STATS -R² score: 0.99999875 -MSE (mean SQR error): 7.043928e-7 -RMSE (Root MSE): 0.0008392811 -MAE (mean ABS error): 0.00037126482 -maxAE (max ABS error) 0.10817945 -Lipschitz bound: 1.8704468e7 - -#======================# diff --git a/examples/burgers_fourier1D/dump/statistics_08.txt b/examples/burgers_fourier1D/dump/statistics_08.txt deleted file mode 100644 index 469edeca..00000000 --- a/examples/burgers_fourier1D/dump/statistics_08.txt +++ /dev/null @@ -1,21 +0,0 @@ -Epoch [0 / 0] TRAIN LOSS: 6.1352684e-6 || TEST LOSS: 6.1352684e-6 -#======================# -TRAIN STATS -R² score: 0.9999993 -MSE (mean SQR error): 4.0967015e-7 -RMSE (Root MSE): 0.0006400548 -MAE (mean ABS error): 0.00032236174 -maxAE (max ABS error) 0.049059033 -Lipschitz bound: 2.1472804e7 - -#======================# -#======================# -TEST STATS -R² score: 0.9999993 -MSE (mean SQR error): 4.0967015e-7 -RMSE (Root MSE): 0.0006400548 -MAE (mean ABS error): 0.00032236174 -maxAE (max ABS error) 0.049059033 -Lipschitz bound: 2.1472804e7 - -#======================# diff --git a/examples/ks_fourier/autodecode.jl b/examples/ks_fourier/autodecode.jl index 4c3c8301..9d3acab6 100644 --- a/examples/ks_fourier/autodecode.jl +++ b/examples/ks_fourier/autodecode.jl @@ -4,26 +4,24 @@ include(joinpath(pkgdir(GeometryLearning), "examples", "autodecoder.jl")) #======================================================# rng = Random.default_rng() -Random.seed!(rng, 123) +Random.seed!(rng, 213) +prob = KuramotoSivashinsky1D(0.01f0) device = Lux.gpu_device() datafile = joinpath(@__DIR__, "data_ks/", "data.jld2") modeldir = joinpath(@__DIR__, "dump") modelfile = joinpath(modeldir, "model_08.jld2") -prob = KuramotoSivashinsky1D(0.01f0) - -E = 2100 # epochs +E = 3500 # epochs l = 16 # latent h = 5 # num hidden w = 128 # width -### WORKS λ1, λ2 = 0f0, 0f0 σ2inv, α = 1f-1, 0f-0 # 1f-1, 1f-3 weight_decays = 1f-2 # 1f-2 -WeightDecayOpt = DecoderWeightDecay -weight_decay_ifunc = nothing +WeightDecayOpt = IdxWeightDecay +weight_decay_ifunc = decoder_W_indices ## train isdir(modeldir) && rm(modeldir, recursive = true) diff --git a/examples/ks_fourier/autodecode1.jl b/examples/ks_fourier/autodecode1.jl index 841b14ca..d2abc498 100644 --- a/examples/ks_fourier/autodecode1.jl +++ b/examples/ks_fourier/autodecode1.jl @@ -4,21 +4,19 @@ include(joinpath(pkgdir(GeometryLearning), "examples", "autodecoder.jl")) #======================================================# rng = Random.default_rng() -Random.seed!(rng, 199) +Random.seed!(rng, 213) +prob = KuramotoSivashinsky1D(0.01f0) device = Lux.gpu_device() datafile = joinpath(@__DIR__, "data_ks/", "data.jld2") modeldir = joinpath(@__DIR__, "dump1") modelfile = joinpath(modeldir, "model_08.jld2") -prob = KuramotoSivashinsky1D(0.01f0) - -E = 2100 # epochs +E = 3500 # epochs l = 16 # latent h = 5 # num hidden w = 128 # width -#### WORKS λ1, λ2 = 0f0, 0f0 σ2inv, α = 1f-1, 0f-0 # 1f-1, 1f-3 weight_decays = 1f-2 # 1f-2 @@ -33,10 +31,9 @@ train_SNF(datafile, modeldir, l, h, w, E; WeightDecayOpt, weight_decay_ifunc, ) -## process -# outdir = joinpath(modeldir, "results") -# postprocess_SNF(prob, datafile, modelfile, outdir; rng, device, -# makeplot = true, verbose = true) +outdir = joinpath(modeldir, "results") +postprocess_SNF(prob, datafile, modelfile, outdir; rng, device, + makeplot = true, verbose = true) x, t, ud, up, _ = evolve_SNF(prob, datafile, modelfile, 1; rng, device, verbose = true) plt = plot(x[1,:], ud[1,:,begin], w = 4, c = :black, label = nothing) plot!(plt, x[1,:], ud[1,:,end ], w = 4, c = :black, label = "data") diff --git a/examples/ks_fourier/compare_l_16.png b/examples/ks_fourier/compare_l_16.png index 97e57a69..1b1873dc 100644 Binary files a/examples/ks_fourier/compare_l_16.png and b/examples/ks_fourier/compare_l_16.png differ diff --git a/examples/ks_fourier/dump/plt_training_01.png 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b/examples/ks_fourier/dump/results/dudx4_334_FWD_AD.png differ diff --git a/examples/ks_fourier/dump/results/dudx4_667_FWD_AD.png b/examples/ks_fourier/dump/results/dudx4_667_FWD_AD.png new file mode 100644 index 00000000..91e60915 Binary files /dev/null and b/examples/ks_fourier/dump/results/dudx4_667_FWD_AD.png differ diff --git a/examples/ks_fourier/dump/results/train_u1_k1.png b/examples/ks_fourier/dump/results/train_u1_k1.png new file mode 100644 index 00000000..6260a139 Binary files /dev/null and b/examples/ks_fourier/dump/results/train_u1_k1.png differ diff --git a/examples/ks_fourier/dump/statistics_01.txt b/examples/ks_fourier/dump/statistics_01.txt index 861c94cb..4b5119d2 100644 --- a/examples/ks_fourier/dump/statistics_01.txt +++ b/examples/ks_fourier/dump/statistics_01.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 0.03630612 || TEST LOSS: 0.03630612 +Epoch [0 / 0] TRAIN LOSS: 0.07588581 || TEST LOSS: 0.07588581 #======================# TRAIN STATS -R² score: 0.9787719 -MSE (mean SQR error): 0.018879171 -RMSE (Root MSE): 0.13740149 -MAE (mean ABS error): 0.08239262 -maxAE (max ABS error) 1.9606904 -Lipschitz bound: 525378.1 +R² score: 0.9277964 +MSE (mean SQR error): 0.05796541 +RMSE (Root MSE): 0.24076006 +MAE (mean ABS error): 0.13095267 +maxAE (max ABS error) 3.4707825 +Lipschitz bound: 2.2992685e6 #======================# #======================# TEST STATS -R² score: 0.9787719 -MSE (mean SQR error): 0.018879173 -RMSE (Root MSE): 0.1374015 -MAE (mean ABS error): 0.08239261 -maxAE (max ABS error) 1.9606904 -Lipschitz bound: 525378.1 +R² score: 0.9277964 +MSE (mean SQR error): 0.0579654 +RMSE (Root MSE): 0.24076004 +MAE (mean ABS error): 0.13095269 +maxAE (max ABS error) 3.4707825 +Lipschitz bound: 2.2992685e6 #======================# diff --git a/examples/ks_fourier/dump/statistics_02.txt b/examples/ks_fourier/dump/statistics_02.txt new file mode 100644 index 00000000..ca6234a6 --- /dev/null +++ b/examples/ks_fourier/dump/statistics_02.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 0.00015286713 || TEST LOSS: 0.00015286713 +#======================# +TRAIN STATS +R² score: 0.9999683 +MSE (mean SQR error): 3.163145e-5 +RMSE (Root MSE): 0.0056241844 +MAE (mean ABS error): 0.0036128324 +maxAE (max ABS error) 0.11503696 +Lipschitz bound: 4.6609924e7 + +#======================# +#======================# +TEST STATS +R² score: 0.9999683 +MSE (mean SQR error): 3.1631454e-5 +RMSE (Root MSE): 0.005624185 +MAE (mean ABS error): 0.0036128324 +maxAE (max ABS error) 0.11503696 +Lipschitz bound: 4.6609924e7 + +#======================# diff --git a/examples/ks_fourier/dump/statistics_03.txt b/examples/ks_fourier/dump/statistics_03.txt new file mode 100644 index 00000000..81561e87 --- /dev/null +++ b/examples/ks_fourier/dump/statistics_03.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 6.7897796e-5 || TEST LOSS: 6.7897796e-5 +#======================# +TRAIN STATS +R² score: 0.99998426 +MSE (mean SQR error): 1.5811667e-5 +RMSE (Root MSE): 0.003976389 +MAE (mean ABS error): 0.002265179 +maxAE (max ABS error) 0.074305534 +Lipschitz bound: 7.659057e7 + +#======================# +#======================# +TEST STATS +R² score: 0.99998426 +MSE (mean SQR error): 1.5811667e-5 +RMSE (Root MSE): 0.003976389 +MAE (mean ABS error): 0.002265179 +maxAE (max ABS error) 0.074305534 +Lipschitz bound: 7.659057e7 + +#======================# diff --git a/examples/ks_fourier/dump/statistics_04.txt b/examples/ks_fourier/dump/statistics_04.txt new file mode 100644 index 00000000..a41f5dff --- /dev/null +++ b/examples/ks_fourier/dump/statistics_04.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 2.2627391e-5 || TEST LOSS: 2.2627393e-5 +#======================# +TRAIN STATS +R² score: 0.99999666 +MSE (mean SQR error): 3.41736e-6 +RMSE (Root MSE): 0.0018486102 +MAE (mean ABS error): 0.0010575661 +maxAE (max ABS error) 0.031131268 +Lipschitz bound: 1.0278369e8 + +#======================# +#======================# +TEST STATS +R² score: 0.99999666 +MSE (mean SQR error): 3.41736e-6 +RMSE (Root MSE): 0.0018486104 +MAE (mean ABS error): 0.001057566 +maxAE (max ABS error) 0.031131268 +Lipschitz bound: 1.0278369e8 + +#======================# diff --git a/examples/ks_fourier/dump/statistics_05.txt b/examples/ks_fourier/dump/statistics_05.txt new file mode 100644 index 00000000..db4ad4ae --- /dev/null +++ b/examples/ks_fourier/dump/statistics_05.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 1.1189979e-5 || TEST LOSS: 1.1189979e-5 +#======================# +TRAIN STATS +R² score: 0.9999982 +MSE (mean SQR error): 1.7066947e-6 +RMSE (Root MSE): 0.0013064052 +MAE (mean ABS error): 0.0007738529 +maxAE (max ABS error) 0.023283482 +Lipschitz bound: 1.2580006e8 + +#======================# +#======================# +TEST STATS +R² score: 0.9999982 +MSE (mean SQR error): 1.7066948e-6 +RMSE (Root MSE): 0.0013064053 +MAE (mean ABS error): 0.0007738528 +maxAE (max ABS error) 0.023283482 +Lipschitz bound: 1.2580006e8 + +#======================# diff --git a/examples/ks_fourier/dump/statistics_06.txt b/examples/ks_fourier/dump/statistics_06.txt new file mode 100644 index 00000000..acd7d4ea --- /dev/null +++ b/examples/ks_fourier/dump/statistics_06.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 6.2228837e-6 || TEST LOSS: 6.2228846e-6 +#======================# +TRAIN STATS +R² score: 0.99999845 +MSE (mean SQR error): 1.5489179e-6 +RMSE (Root MSE): 0.0012445553 +MAE (mean ABS error): 0.0007334761 +maxAE (max ABS error) 0.023916245 +Lipschitz bound: 1.5948907e8 + +#======================# +#======================# +TEST STATS +R² score: 0.99999845 +MSE (mean SQR error): 1.5489181e-6 +RMSE (Root MSE): 0.0012445553 +MAE (mean ABS error): 0.0007334762 +maxAE (max ABS error) 0.023916245 +Lipschitz bound: 1.5948907e8 + +#======================# diff --git a/examples/ks_fourier/dump/statistics_07.txt b/examples/ks_fourier/dump/statistics_07.txt new file mode 100644 index 00000000..b0265114 --- /dev/null +++ b/examples/ks_fourier/dump/statistics_07.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 3.4701893e-6 || TEST LOSS: 3.4701893e-6 +#======================# +TRAIN STATS +R² score: 0.9999992 +MSE (mean SQR error): 8.52025e-7 +RMSE (Root MSE): 0.00092305196 +MAE (mean ABS error): 0.0005729576 +maxAE (max ABS error) 0.018838406 +Lipschitz bound: 1.9000798e8 + +#======================# +#======================# +TEST STATS +R² score: 0.9999992 +MSE (mean SQR error): 8.5202504e-7 +RMSE (Root MSE): 0.000923052 +MAE (mean ABS error): 0.0005729576 +maxAE (max ABS error) 0.018838406 +Lipschitz bound: 1.9000798e8 + +#======================# diff --git a/examples/ks_fourier/dump/statistics_08.txt b/examples/ks_fourier/dump/statistics_08.txt new file mode 100644 index 00000000..427e1924 --- /dev/null +++ b/examples/ks_fourier/dump/statistics_08.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 2.5187164e-6 || TEST LOSS: 2.5187164e-6 +#======================# +TRAIN STATS +R² score: 0.99999946 +MSE (mean SQR error): 5.2832337e-7 +RMSE (Root MSE): 0.00072685856 +MAE (mean ABS error): 0.0004764152 +maxAE (max ABS error) 0.014974236 +Lipschitz bound: 2.046892e8 + +#======================# +#======================# +TEST STATS +R² score: 0.99999946 +MSE (mean SQR error): 5.2832337e-7 +RMSE (Root MSE): 0.00072685856 +MAE (mean ABS error): 0.00047641518 +maxAE (max ABS error) 0.014974236 +Lipschitz bound: 2.046892e8 + +#======================# diff --git a/examples/ks_fourier/dump1/plt_training_01.png b/examples/ks_fourier/dump1/plt_training_01.png index dc205905..697df9a7 100644 Binary files a/examples/ks_fourier/dump1/plt_training_01.png and b/examples/ks_fourier/dump1/plt_training_01.png differ diff --git a/examples/ks_fourier/dump1/plt_training_02.png b/examples/ks_fourier/dump1/plt_training_02.png new file mode 100644 index 00000000..338445e8 Binary files /dev/null and b/examples/ks_fourier/dump1/plt_training_02.png differ diff --git a/examples/ks_fourier/dump1/plt_training_03.png 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mode 100644 index 00000000..b2746e83 Binary files /dev/null and b/examples/ks_fourier/dump1/plt_training_07.png differ diff --git a/examples/ks_fourier/dump1/plt_training_08.png b/examples/ks_fourier/dump1/plt_training_08.png new file mode 100644 index 00000000..a829c325 Binary files /dev/null and b/examples/ks_fourier/dump1/plt_training_08.png differ diff --git a/examples/ks_fourier/dump1/results/README.md b/examples/ks_fourier/dump1/results/README.md new file mode 100644 index 00000000..bdbdd01d --- /dev/null +++ b/examples/ks_fourier/dump1/results/README.md @@ -0,0 +1 @@ +Train/test on the same trajectory. \ No newline at end of file diff --git a/examples/ks_fourier/dump1/results/dudx1_1000_FWD_AD.png b/examples/ks_fourier/dump1/results/dudx1_1000_FWD_AD.png new file mode 100644 index 00000000..2d7f40b5 Binary files /dev/null and b/examples/ks_fourier/dump1/results/dudx1_1000_FWD_AD.png differ diff --git a/examples/ks_fourier/dump1/results/dudx1_1_FWD_AD.png 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00000000..377a47d4 Binary files /dev/null and b/examples/ks_fourier/dump1/results/dudx4_1000_FWD_AD.png differ diff --git a/examples/ks_fourier/dump1/results/dudx4_1_FWD_AD.png b/examples/ks_fourier/dump1/results/dudx4_1_FWD_AD.png new file mode 100644 index 00000000..65d9fe5e Binary files /dev/null and b/examples/ks_fourier/dump1/results/dudx4_1_FWD_AD.png differ diff --git a/examples/ks_fourier/dump1/results/dudx4_334_FWD_AD.png b/examples/ks_fourier/dump1/results/dudx4_334_FWD_AD.png new file mode 100644 index 00000000..acda84c5 Binary files /dev/null and b/examples/ks_fourier/dump1/results/dudx4_334_FWD_AD.png differ diff --git a/examples/ks_fourier/dump1/results/dudx4_667_FWD_AD.png b/examples/ks_fourier/dump1/results/dudx4_667_FWD_AD.png new file mode 100644 index 00000000..95bc20ee Binary files /dev/null and b/examples/ks_fourier/dump1/results/dudx4_667_FWD_AD.png differ diff --git a/examples/ks_fourier/dump1/results/train_u1_k1.png b/examples/ks_fourier/dump1/results/train_u1_k1.png new file mode 100644 index 00000000..58b4be01 Binary files /dev/null and b/examples/ks_fourier/dump1/results/train_u1_k1.png differ diff --git a/examples/ks_fourier/dump1/statistics_01.txt b/examples/ks_fourier/dump1/statistics_01.txt index 6b327599..88b83618 100644 --- a/examples/ks_fourier/dump1/statistics_01.txt +++ b/examples/ks_fourier/dump1/statistics_01.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 0.044135064 || TEST LOSS: 0.044135064 +Epoch [0 / 0] TRAIN LOSS: 0.026706614 || TEST LOSS: 0.026706615 #======================# TRAIN STATS -R² score: 0.9685681 -MSE (mean SQR error): 0.027702006 -RMSE (Root MSE): 0.16643919 -MAE (mean ABS error): 0.0970701 -maxAE (max ABS error) 2.228157 -Lipschitz bound: 1.4755941e6 +R² score: 0.98470813 +MSE (mean SQR error): 0.014894791 +RMSE (Root MSE): 0.12204422 +MAE (mean ABS error): 0.061318178 +maxAE (max ABS error) 2.0699325 +Lipschitz bound: 2.063712e6 #======================# #======================# TEST STATS -R² score: 0.9685681 -MSE (mean SQR error): 0.027702006 -RMSE (Root MSE): 0.16643919 -MAE (mean ABS error): 0.0970701 -maxAE (max ABS error) 2.228157 -Lipschitz bound: 1.4755941e6 +R² score: 0.98470813 +MSE (mean SQR error): 0.014894793 +RMSE (Root MSE): 0.12204423 +MAE (mean ABS error): 0.061318178 +maxAE (max ABS error) 2.0699325 +Lipschitz bound: 2.063712e6 #======================# diff --git a/examples/ks_fourier/dump1/statistics_02.txt b/examples/ks_fourier/dump1/statistics_02.txt new file mode 100644 index 00000000..eba954aa --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_02.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 0.00017549968 || TEST LOSS: 0.00017549968 +#======================# +TRAIN STATS +R² score: 0.9999402 +MSE (mean SQR error): 5.981315e-5 +RMSE (Root MSE): 0.007733896 +MAE (mean ABS error): 0.0052265595 +maxAE (max ABS error) 0.1427741 +Lipschitz bound: 9.65411e6 + +#======================# +#======================# +TEST STATS +R² score: 0.9999402 +MSE (mean SQR error): 5.9813145e-5 +RMSE (Root MSE): 0.007733896 +MAE (mean ABS error): 0.00522656 +maxAE (max ABS error) 0.1427741 +Lipschitz bound: 9.65411e6 + +#======================# diff --git a/examples/ks_fourier/dump1/statistics_03.txt b/examples/ks_fourier/dump1/statistics_03.txt new file mode 100644 index 00000000..1d968063 --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_03.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 7.3288655e-5 || TEST LOSS: 7.328867e-5 +#======================# +TRAIN STATS +R² score: 0.9999832 +MSE (mean SQR error): 1.6801978e-5 +RMSE (Root MSE): 0.0040990217 +MAE (mean ABS error): 0.002458472 +maxAE (max ABS error) 0.07296085 +Lipschitz bound: 1.1120675e7 + +#======================# +#======================# +TEST STATS +R² score: 0.9999832 +MSE (mean SQR error): 1.6801978e-5 +RMSE (Root MSE): 0.0040990217 +MAE (mean ABS error): 0.0024584718 +maxAE (max ABS error) 0.07296085 +Lipschitz bound: 1.1120675e7 + +#======================# diff --git a/examples/ks_fourier/dump1/statistics_04.txt b/examples/ks_fourier/dump1/statistics_04.txt new file mode 100644 index 00000000..0d4e3ba3 --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_04.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 3.2084863e-5 || TEST LOSS: 3.2084863e-5 +#======================# +TRAIN STATS +R² score: 0.9999912 +MSE (mean SQR error): 8.846877e-6 +RMSE (Root MSE): 0.00297437 +MAE (mean ABS error): 0.0016458192 +maxAE (max ABS error) 0.06928873 +Lipschitz bound: 1.390834e7 + +#======================# +#======================# +TEST STATS +R² score: 0.9999912 +MSE (mean SQR error): 8.846876e-6 +RMSE (Root MSE): 0.0029743698 +MAE (mean ABS error): 0.0016458192 +maxAE (max ABS error) 0.06928873 +Lipschitz bound: 1.390834e7 + +#======================# diff --git a/examples/ks_fourier/dump1/statistics_05.txt b/examples/ks_fourier/dump1/statistics_05.txt new file mode 100644 index 00000000..a82da3ac --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_05.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 1.8835635e-5 || TEST LOSS: 1.8835635e-5 +#======================# +TRAIN STATS +R² score: 0.9999946 +MSE (mean SQR error): 5.400916e-6 +RMSE (Root MSE): 0.0023239872 +MAE (mean ABS error): 0.0013400972 +maxAE (max ABS error) 0.052418947 +Lipschitz bound: 1.6673363e7 + +#======================# +#======================# +TEST STATS +R² score: 0.9999946 +MSE (mean SQR error): 5.400915e-6 +RMSE (Root MSE): 0.002323987 +MAE (mean ABS error): 0.0013400974 +maxAE (max ABS error) 0.052418947 +Lipschitz bound: 1.6673363e7 + +#======================# diff --git a/examples/ks_fourier/dump1/statistics_06.txt b/examples/ks_fourier/dump1/statistics_06.txt new file mode 100644 index 00000000..5ec19f00 --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_06.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 9.456895e-6 || TEST LOSS: 9.456895e-6 +#======================# +TRAIN STATS +R² score: 0.9999969 +MSE (mean SQR error): 3.090851e-6 +RMSE (Root MSE): 0.0017580816 +MAE (mean ABS error): 0.0010567248 +maxAE (max ABS error) 0.0376997 +Lipschitz bound: 2.3642146e7 + +#======================# +#======================# +TEST STATS +R² score: 0.9999969 +MSE (mean SQR error): 3.090851e-6 +RMSE (Root MSE): 0.0017580816 +MAE (mean ABS error): 0.0010567249 +maxAE (max ABS error) 0.0376997 +Lipschitz bound: 2.3642146e7 + +#======================# diff --git a/examples/ks_fourier/dump1/statistics_07.txt b/examples/ks_fourier/dump1/statistics_07.txt new file mode 100644 index 00000000..95970d5d --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_07.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 5.827547e-6 || TEST LOSS: 5.827547e-6 +#======================# +TRAIN STATS +R² score: 0.999998 +MSE (mean SQR error): 2.0020473e-6 +RMSE (Root MSE): 0.0014149372 +MAE (mean ABS error): 0.00089832844 +maxAE (max ABS error) 0.025701761 +Lipschitz bound: 3.0297504e7 + +#======================# +#======================# +TEST STATS +R² score: 0.999998 +MSE (mean SQR error): 2.002047e-6 +RMSE (Root MSE): 0.0014149371 +MAE (mean ABS error): 0.0008983283 +maxAE (max ABS error) 0.025701761 +Lipschitz bound: 3.0297504e7 + +#======================# diff --git a/examples/ks_fourier/dump1/statistics_08.txt b/examples/ks_fourier/dump1/statistics_08.txt new file mode 100644 index 00000000..6ea2d67b --- /dev/null +++ b/examples/ks_fourier/dump1/statistics_08.txt @@ -0,0 +1,21 @@ +Epoch [0 / 0] TRAIN LOSS: 4.1977028e-6 || TEST LOSS: 4.1977028e-6 +#======================# +TRAIN STATS +R² score: 0.9999986 +MSE (mean SQR error): 1.3826623e-6 +RMSE (Root MSE): 0.0011758666 +MAE (mean ABS error): 0.0007874248 +maxAE (max ABS error) 0.022046208 +Lipschitz bound: 3.502102e7 + +#======================# +#======================# +TEST STATS +R² score: 0.9999986 +MSE (mean SQR error): 1.3826622e-6 +RMSE (Root MSE): 0.0011758666 +MAE (mean ABS error): 0.0007874249 +maxAE (max ABS error) 0.022046208 +Lipschitz bound: 3.502102e7 + +#======================# diff --git a/examples/ks_fourier/ks1d.npz b/examples/ks_fourier/ks1d.npz index 135c2d82..99b21b03 100644 Binary files a/examples/ks_fourier/ks1d.npz and b/examples/ks_fourier/ks1d.npz differ diff --git a/examples/ks_fourier/ks1d_compare.jl b/examples/ks_fourier/ks1d_compare.jl index 03c1d3b1..6e77afa9 100644 --- a/examples/ks_fourier/ks1d_compare.jl +++ b/examples/ks_fourier/ks1d_compare.jl @@ -39,8 +39,8 @@ function ks1d_train_SNFW( w = 128 # width λ1, λ2 = 0f0, 0f0 # L1 / L2 reg - σ2inv, α = 1f-2, 0f-0 # code / Lipschitz regularization - weight_decays = 1f-1 # AdamW weight decay + σ2inv, α = 1f-1, 0f-0 # code / Lipschitz regularization + weight_decays = 1f-2 # AdamW weight decay train_SNF(datafile, modeldir, l, h, w, E; rng, warmup = true, @@ -57,8 +57,12 @@ function ks1d_train_SNFL( h = 5 # num hidden w = 128 # width + # λ1, λ2 = 0f0, 0f0 # L1 / L2 reg + # σ2inv, α = 1f-2, 5f-4 # code / Lipschitz regularization + # weight_decays = 0f-0 # AdamW weight decay + λ1, λ2 = 0f0, 0f0 # L1 / L2 reg - σ2inv, α = 1f-2, 5f-4 # code / Lipschitz regularization + σ2inv, α = 1f-1, 1f-3 # code / Lipschitz regularization weight_decays = 0f-0 # AdamW weight decay train_SNF( @@ -89,8 +93,8 @@ modeldir_SNFW = joinpath(@__DIR__, "model_SNFW_l_$(ll)") modeldir_SNFL = joinpath(@__DIR__, "model_SNFL_l_$(ll)") # ks1d_train_CINR(latent, modeldir_CINR; device) -# ks1d_train_SNFW(latent, modeldir_SNFW; device) -# ks1d_train_SNFL(latent, modeldir_SNFL; device) +ks1d_train_SNFW(latent, modeldir_SNFW; device) +ks1d_train_SNFL(latent, modeldir_SNFL; device) #==================# # evolve diff --git a/examples/ks_fourier/model_SNFL_l_16/plt_training_01.png b/examples/ks_fourier/model_SNFL_l_16/plt_training_01.png index f4c06754..1869b415 100644 Binary files a/examples/ks_fourier/model_SNFL_l_16/plt_training_01.png and b/examples/ks_fourier/model_SNFL_l_16/plt_training_01.png differ diff --git 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b/examples/ks_fourier/model_SNFL_l_16/plt_training_05.png index f83e7fed..6ff9fc8c 100644 Binary files a/examples/ks_fourier/model_SNFL_l_16/plt_training_05.png and b/examples/ks_fourier/model_SNFL_l_16/plt_training_05.png differ diff --git a/examples/ks_fourier/model_SNFL_l_16/plt_training_06.png b/examples/ks_fourier/model_SNFL_l_16/plt_training_06.png index 8b2056b6..b9f9b700 100644 Binary files a/examples/ks_fourier/model_SNFL_l_16/plt_training_06.png and b/examples/ks_fourier/model_SNFL_l_16/plt_training_06.png differ diff --git a/examples/ks_fourier/model_SNFL_l_16/plt_training_07.png b/examples/ks_fourier/model_SNFL_l_16/plt_training_07.png index bfa80d48..417115fb 100644 Binary files a/examples/ks_fourier/model_SNFL_l_16/plt_training_07.png and b/examples/ks_fourier/model_SNFL_l_16/plt_training_07.png differ diff --git a/examples/ks_fourier/model_SNFL_l_16/plt_training_08.png b/examples/ks_fourier/model_SNFL_l_16/plt_training_08.png index 57f43121..54a19e89 100644 Binary files a/examples/ks_fourier/model_SNFL_l_16/plt_training_08.png and b/examples/ks_fourier/model_SNFL_l_16/plt_training_08.png differ diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_01.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_01.txt index 70e6a43a..8a938840 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_01.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_01.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 1.0027251 || TEST LOSS: 1.002725 +Epoch [0 / 0] TRAIN LOSS: 1.004523 || TEST LOSS: 1.0045229 #======================# TRAIN STATS -R² score: -5.414584e6 -MSE (mean SQR error): 1.000014 -RMSE (Root MSE): 1.0000069 -MAE (mean ABS error): 0.48856997 -maxAE (max ABS error) 7.3447137 -Lipschitz bound: 484513.38 +R² score: -4.937085e6 +MSE (mean SQR error): 1.0000246 +RMSE (Root MSE): 1.0000123 +MAE (mean ABS error): 0.49188915 +maxAE (max ABS error) 7.339717 +Lipschitz bound: 440493.7 #======================# #======================# TEST STATS -R² score: -5.414584e6 -MSE (mean SQR error): 1.0000138 -RMSE (Root MSE): 1.0000069 -MAE (mean ABS error): 0.48856992 -maxAE (max ABS error) 7.3447137 -Lipschitz bound: 484513.38 +R² score: -4.9370855e6 +MSE (mean SQR error): 1.0000246 +RMSE (Root MSE): 1.0000123 +MAE (mean ABS error): 0.49188915 +maxAE (max ABS error) 7.339717 +Lipschitz bound: 440493.7 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_02.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_02.txt index fad1fc2b..98ef37dc 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_02.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_02.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 0.0002191036 || TEST LOSS: 0.0002191036 +Epoch [0 / 0] TRAIN LOSS: 0.00032657152 || TEST LOSS: 0.00032657152 #======================# TRAIN STATS -R² score: 0.9998943 -MSE (mean SQR error): 0.000105022424 -RMSE (Root MSE): 0.010248045 -MAE (mean ABS error): 0.0056058634 -maxAE (max ABS error) 0.25911283 -Lipschitz bound: 3723.8923 +R² score: 0.9998796 +MSE (mean SQR error): 0.00011998231 +RMSE (Root MSE): 0.010953644 +MAE (mean ABS error): 0.005768932 +maxAE (max ABS error) 0.32857752 +Lipschitz bound: 2562.0977 #======================# #======================# TEST STATS -R² score: 0.9998943 -MSE (mean SQR error): 0.000105022424 -RMSE (Root MSE): 0.010248045 -MAE (mean ABS error): 0.0056058634 -maxAE (max ABS error) 0.25911283 -Lipschitz bound: 3723.8923 +R² score: 0.9998796 +MSE (mean SQR error): 0.00011998231 +RMSE (Root MSE): 0.010953643 +MAE (mean ABS error): 0.005768932 +maxAE (max ABS error) 0.32857752 +Lipschitz bound: 2562.0977 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_03.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_03.txt index e9ff0e2c..7e85ec5e 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_03.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_03.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 0.00012116761 || TEST LOSS: 0.00012116761 +Epoch [0 / 0] TRAIN LOSS: 0.00015710898 || TEST LOSS: 0.00015710898 #======================# TRAIN STATS -R² score: 0.9999581 -MSE (mean SQR error): 4.191755e-5 -RMSE (Root MSE): 0.006474376 -MAE (mean ABS error): 0.0042254073 -maxAE (max ABS error) 0.14230776 -Lipschitz bound: 1879.445 +R² score: 0.9999394 +MSE (mean SQR error): 6.077635e-5 +RMSE (Root MSE): 0.0077959183 +MAE (mean ABS error): 0.0052659265 +maxAE (max ABS error) 0.13098979 +Lipschitz bound: 935.962 #======================# #======================# TEST STATS -R² score: 0.9999581 -MSE (mean SQR error): 4.191755e-5 -RMSE (Root MSE): 0.006474376 -MAE (mean ABS error): 0.0042254073 -maxAE (max ABS error) 0.14230776 -Lipschitz bound: 1879.445 +R² score: 0.9999394 +MSE (mean SQR error): 6.0776347e-5 +RMSE (Root MSE): 0.0077959183 +MAE (mean ABS error): 0.005265926 +maxAE (max ABS error) 0.13098979 +Lipschitz bound: 935.962 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_04.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_04.txt index 18da9931..750c9916 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_04.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_04.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 8.155123e-5 || TEST LOSS: 8.155123e-5 +Epoch [0 / 0] TRAIN LOSS: 7.8410674e-5 || TEST LOSS: 7.8410674e-5 #======================# TRAIN STATS -R² score: 0.9999794 -MSE (mean SQR error): 2.0615944e-5 -RMSE (Root MSE): 0.0045404783 -MAE (mean ABS error): 0.0030946988 -maxAE (max ABS error) 0.09032124 -Lipschitz bound: 1132.258 +R² score: 0.9999777 +MSE (mean SQR error): 2.232227e-5 +RMSE (Root MSE): 0.004724645 +MAE (mean ABS error): 0.0030122595 +maxAE (max ABS error) 0.13817072 +Lipschitz bound: 585.176 #======================# #======================# TEST STATS -R² score: 0.9999794 -MSE (mean SQR error): 2.0615944e-5 -RMSE (Root MSE): 0.0045404783 -MAE (mean ABS error): 0.0030946985 -maxAE (max ABS error) 0.09032124 -Lipschitz bound: 1132.258 +R² score: 0.9999777 +MSE (mean SQR error): 2.2322269e-5 +RMSE (Root MSE): 0.004724645 +MAE (mean ABS error): 0.0030122595 +maxAE (max ABS error) 0.13817072 +Lipschitz bound: 585.176 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_05.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_05.txt index c449cbbf..a1183229 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_05.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_05.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 6.997131e-5 || TEST LOSS: 6.997132e-5 +Epoch [0 / 0] TRAIN LOSS: 5.596163e-5 || TEST LOSS: 5.596163e-5 #======================# TRAIN STATS -R² score: 0.9999908 -MSE (mean SQR error): 9.19796e-6 -RMSE (Root MSE): 0.0030328138 -MAE (mean ABS error): 0.0016507248 -maxAE (max ABS error) 0.093427464 -Lipschitz bound: 1089.9023 +R² score: 0.9999891 +MSE (mean SQR error): 1.0815469e-5 +RMSE (Root MSE): 0.0032886881 +MAE (mean ABS error): 0.0019804272 +maxAE (max ABS error) 0.051614285 +Lipschitz bound: 486.5752 #======================# #======================# TEST STATS -R² score: 0.9999908 -MSE (mean SQR error): 9.197962e-6 -RMSE (Root MSE): 0.0030328142 -MAE (mean ABS error): 0.0016507248 -maxAE (max ABS error) 0.093427464 -Lipschitz bound: 1089.9023 +R² score: 0.9999891 +MSE (mean SQR error): 1.0815467e-5 +RMSE (Root MSE): 0.0032886877 +MAE (mean ABS error): 0.0019804272 +maxAE (max ABS error) 0.051614285 +Lipschitz bound: 486.5752 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_06.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_06.txt index c7023342..ee3da02d 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_06.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_06.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 6.310305e-5 || TEST LOSS: 6.310304e-5 +Epoch [0 / 0] TRAIN LOSS: 4.7402824e-5 || TEST LOSS: 4.7402824e-5 #======================# TRAIN STATS -R² score: 0.9999919 -MSE (mean SQR error): 8.122519e-6 -RMSE (Root MSE): 0.0028500033 -MAE (mean ABS error): 0.0017374586 -maxAE (max ABS error) 0.07075556 -Lipschitz bound: 914.4449 +R² score: 0.999993 +MSE (mean SQR error): 6.9514904e-6 +RMSE (Root MSE): 0.002636568 +MAE (mean ABS error): 0.0016443466 +maxAE (max ABS error) 0.044098858 +Lipschitz bound: 446.56897 #======================# #======================# TEST STATS -R² score: 0.9999919 -MSE (mean SQR error): 8.122518e-6 -RMSE (Root MSE): 0.002850003 -MAE (mean ABS error): 0.0017374586 -maxAE (max ABS error) 0.07075556 -Lipschitz bound: 914.4449 +R² score: 0.999993 +MSE (mean SQR error): 6.9514904e-6 +RMSE (Root MSE): 0.002636568 +MAE (mean ABS error): 0.0016443466 +maxAE (max ABS error) 0.044098858 +Lipschitz bound: 446.56897 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_07.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_07.txt index 434e495c..15bf833d 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_07.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_07.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 5.9508282e-5 || TEST LOSS: 5.9508282e-5 +Epoch [0 / 0] TRAIN LOSS: 4.3651005e-5 || TEST LOSS: 4.3651005e-5 #======================# TRAIN STATS -R² score: 0.99999386 -MSE (mean SQR error): 6.151227e-6 -RMSE (Root MSE): 0.0024801667 -MAE (mean ABS error): 0.0013974808 -maxAE (max ABS error) 0.07050805 -Lipschitz bound: 857.4098 +R² score: 0.9999949 +MSE (mean SQR error): 5.1455927e-6 +RMSE (Root MSE): 0.0022683898 +MAE (mean ABS error): 0.0013975905 +maxAE (max ABS error) 0.039242744 +Lipschitz bound: 428.51077 #======================# #======================# TEST STATS -R² score: 0.99999386 -MSE (mean SQR error): 6.1512264e-6 -RMSE (Root MSE): 0.0024801667 -MAE (mean ABS error): 0.0013974807 -maxAE (max ABS error) 0.07050805 -Lipschitz bound: 857.4098 +R² score: 0.9999949 +MSE (mean SQR error): 5.145593e-6 +RMSE (Root MSE): 0.00226839 +MAE (mean ABS error): 0.0013975906 +maxAE (max ABS error) 0.039242744 +Lipschitz bound: 428.51077 #======================# diff --git a/examples/ks_fourier/model_SNFL_l_16/statistics_08.txt b/examples/ks_fourier/model_SNFL_l_16/statistics_08.txt index e77494f5..62f63098 100644 --- a/examples/ks_fourier/model_SNFL_l_16/statistics_08.txt +++ b/examples/ks_fourier/model_SNFL_l_16/statistics_08.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 5.8230075e-5 || TEST LOSS: 5.8230085e-5 +Epoch [0 / 0] TRAIN LOSS: 4.2364223e-5 || TEST LOSS: 4.236422e-5 #======================# TRAIN STATS -R² score: 0.99999446 -MSE (mean SQR error): 5.51483e-6 -RMSE (Root MSE): 0.0023483676 -MAE (mean ABS error): 0.0012243115 -maxAE (max ABS error) 0.06914073 -Lipschitz bound: 833.2822 +R² score: 0.99999535 +MSE (mean SQR error): 4.6221776e-6 +RMSE (Root MSE): 0.002149925 +MAE (mean ABS error): 0.0013150219 +maxAE (max ABS error) 0.037418365 +Lipschitz bound: 419.94547 #======================# #======================# TEST STATS -R² score: 0.99999446 -MSE (mean SQR error): 5.51483e-6 -RMSE (Root MSE): 0.0023483676 -MAE (mean ABS error): 0.0012243114 -maxAE (max ABS error) 0.06914073 -Lipschitz bound: 833.2822 +R² score: 0.99999535 +MSE (mean SQR error): 4.6221776e-6 +RMSE (Root MSE): 0.002149925 +MAE (mean ABS error): 0.0013150219 +maxAE (max ABS error) 0.037418365 +Lipschitz bound: 419.94547 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/plt_training_01.png b/examples/ks_fourier/model_SNFW_l_16/plt_training_01.png index e5980bad..3491b947 100644 Binary files a/examples/ks_fourier/model_SNFW_l_16/plt_training_01.png and b/examples/ks_fourier/model_SNFW_l_16/plt_training_01.png differ diff --git a/examples/ks_fourier/model_SNFW_l_16/plt_training_02.png b/examples/ks_fourier/model_SNFW_l_16/plt_training_02.png index a40360b9..74ad12c5 100644 Binary files a/examples/ks_fourier/model_SNFW_l_16/plt_training_02.png and 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a/examples/ks_fourier/model_SNFW_l_16/plt_training_06.png b/examples/ks_fourier/model_SNFW_l_16/plt_training_06.png index 5c4849b1..bfe0b6c3 100644 Binary files a/examples/ks_fourier/model_SNFW_l_16/plt_training_06.png and b/examples/ks_fourier/model_SNFW_l_16/plt_training_06.png differ diff --git a/examples/ks_fourier/model_SNFW_l_16/plt_training_07.png b/examples/ks_fourier/model_SNFW_l_16/plt_training_07.png index 6e3dfcbe..8570cc15 100644 Binary files a/examples/ks_fourier/model_SNFW_l_16/plt_training_07.png and b/examples/ks_fourier/model_SNFW_l_16/plt_training_07.png differ diff --git a/examples/ks_fourier/model_SNFW_l_16/plt_training_08.png b/examples/ks_fourier/model_SNFW_l_16/plt_training_08.png index a4c71dc7..05083936 100644 Binary files a/examples/ks_fourier/model_SNFW_l_16/plt_training_08.png and b/examples/ks_fourier/model_SNFW_l_16/plt_training_08.png differ diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_01.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_01.txt index 4a6bb9dd..2fb7c048 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_01.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_01.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 0.073995315 || TEST LOSS: 0.073995315 +Epoch [0 / 0] TRAIN LOSS: 0.04916838 || TEST LOSS: 0.04916838 #======================# TRAIN STATS -R² score: 0.91687024 -MSE (mean SQR error): 0.0713854 -RMSE (Root MSE): 0.26718047 -MAE (mean ABS error): 0.16303353 -maxAE (max ABS error) 3.1075063 -Lipschitz bound: 4.195689e6 +R² score: 0.9639403 +MSE (mean SQR error): 0.032674994 +RMSE (Root MSE): 0.18076226 +MAE (mean ABS error): 0.0806742 +maxAE (max ABS error) 2.4009128 +Lipschitz bound: 1.7715952e6 #======================# #======================# TEST STATS -R² score: 0.91687024 -MSE (mean SQR error): 0.07138539 -RMSE (Root MSE): 0.26718044 -MAE (mean ABS error): 0.16303353 -maxAE (max ABS error) 3.1075063 -Lipschitz bound: 4.195689e6 +R² score: 0.9639403 +MSE (mean SQR error): 0.032674994 +RMSE (Root MSE): 0.18076226 +MAE (mean ABS error): 0.0806742 +maxAE (max ABS error) 2.4009128 +Lipschitz bound: 1.7715952e6 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_02.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_02.txt index 1a796f1f..44184ee5 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_02.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_02.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 6.444641e-5 || TEST LOSS: 6.4446416e-5 +Epoch [0 / 0] TRAIN LOSS: 0.000120381796 || TEST LOSS: 0.000120381796 #======================# TRAIN STATS -R² score: 0.9999891 -MSE (mean SQR error): 1.0907503e-5 -RMSE (Root MSE): 0.0033026508 -MAE (mean ABS error): 0.0018143288 -maxAE (max ABS error) 0.11491537 -Lipschitz bound: 5.058526e7 +R² score: 0.9999699 +MSE (mean SQR error): 3.009627e-5 +RMSE (Root MSE): 0.005486007 +MAE (mean ABS error): 0.0026507094 +maxAE (max ABS error) 0.1540699 +Lipschitz bound: 5.417544e7 #======================# #======================# TEST STATS -R² score: 0.9999891 -MSE (mean SQR error): 1.0907502e-5 -RMSE (Root MSE): 0.0033026508 -MAE (mean ABS error): 0.0018143288 -maxAE (max ABS error) 0.11491537 -Lipschitz bound: 5.058526e7 +R² score: 0.9999699 +MSE (mean SQR error): 3.0096267e-5 +RMSE (Root MSE): 0.0054860064 +MAE (mean ABS error): 0.0026507096 +maxAE (max ABS error) 0.1540699 +Lipschitz bound: 5.417544e7 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_03.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_03.txt index 8cd7027d..29a895b4 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_03.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_03.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 2.3755787e-5 || TEST LOSS: 2.3755787e-5 +Epoch [0 / 0] TRAIN LOSS: 5.3573614e-5 || TEST LOSS: 5.3573614e-5 #======================# TRAIN STATS -R² score: 0.9999963 -MSE (mean SQR error): 3.6879521e-6 -RMSE (Root MSE): 0.0019204041 -MAE (mean ABS error): 0.0011634927 -maxAE (max ABS error) 0.052892685 -Lipschitz bound: 6.5781532e7 +R² score: 0.99999326 +MSE (mean SQR error): 6.7213914e-6 +RMSE (Root MSE): 0.0025925646 +MAE (mean ABS error): 0.0014282946 +maxAE (max ABS error) 0.044136047 +Lipschitz bound: 6.924162e7 #======================# #======================# TEST STATS -R² score: 0.9999963 -MSE (mean SQR error): 3.6879521e-6 -RMSE (Root MSE): 0.0019204041 -MAE (mean ABS error): 0.0011634928 -maxAE (max ABS error) 0.052892685 -Lipschitz bound: 6.5781532e7 +R² score: 0.99999326 +MSE (mean SQR error): 6.7213914e-6 +RMSE (Root MSE): 0.0025925646 +MAE (mean ABS error): 0.0014282945 +maxAE (max ABS error) 0.044136047 +Lipschitz bound: 6.924162e7 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_04.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_04.txt index 96aaa05b..df860a73 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_04.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_04.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 8.81539e-6 || TEST LOSS: 8.81539e-6 +Epoch [0 / 0] TRAIN LOSS: 1.8785184e-5 || TEST LOSS: 1.8785182e-5 #======================# TRAIN STATS -R² score: 0.99999875 -MSE (mean SQR error): 1.2229684e-6 -RMSE (Root MSE): 0.0011058791 -MAE (mean ABS error): 0.0007040042 -maxAE (max ABS error) 0.026517868 -Lipschitz bound: 7.8299096e7 +R² score: 0.999997 +MSE (mean SQR error): 2.9759628e-6 +RMSE (Root MSE): 0.0017250978 +MAE (mean ABS error): 0.0009050923 +maxAE (max ABS error) 0.04121828 +Lipschitz bound: 1.1017126e8 #======================# #======================# TEST STATS -R² score: 0.99999875 -MSE (mean SQR error): 1.2229685e-6 -RMSE (Root MSE): 0.0011058791 -MAE (mean ABS error): 0.00070400425 -maxAE (max ABS error) 0.026517868 -Lipschitz bound: 7.8299096e7 +R² score: 0.999997 +MSE (mean SQR error): 2.975963e-6 +RMSE (Root MSE): 0.001725098 +MAE (mean ABS error): 0.0009050923 +maxAE (max ABS error) 0.04121828 +Lipschitz bound: 1.1017126e8 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_05.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_05.txt index aacecb34..a59afa6b 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_05.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_05.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 4.2030615e-6 || TEST LOSS: 4.203061e-6 +Epoch [0 / 0] TRAIN LOSS: 8.645098e-6 || TEST LOSS: 8.6451e-6 #======================# TRAIN STATS -R² score: 0.9999992 -MSE (mean SQR error): 7.6197585e-7 -RMSE (Root MSE): 0.00087291223 -MAE (mean ABS error): 0.00056563615 -maxAE (max ABS error) 0.018558025 -Lipschitz bound: 8.994436e7 +R² score: 0.99999845 +MSE (mean SQR error): 1.4783859e-6 +RMSE (Root MSE): 0.0012158889 +MAE (mean ABS error): 0.00067222404 +maxAE (max ABS error) 0.042567015 +Lipschitz bound: 1.4962504e8 #======================# #======================# TEST STATS -R² score: 0.9999992 -MSE (mean SQR error): 7.6197585e-7 -RMSE (Root MSE): 0.00087291223 -MAE (mean ABS error): 0.00056563615 -maxAE (max ABS error) 0.018558025 -Lipschitz bound: 8.994436e7 +R² score: 0.99999845 +MSE (mean SQR error): 1.4783859e-6 +RMSE (Root MSE): 0.0012158889 +MAE (mean ABS error): 0.00067222404 +maxAE (max ABS error) 0.042567015 +Lipschitz bound: 1.4962504e8 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_06.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_06.txt index f0bca720..fd75a010 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_06.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_06.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 2.6437574e-6 || TEST LOSS: 2.6437574e-6 +Epoch [0 / 0] TRAIN LOSS: 4.6559458e-6 || TEST LOSS: 4.6559453e-6 #======================# TRAIN STATS -R² score: 0.99999946 -MSE (mean SQR error): 5.813681e-7 -RMSE (Root MSE): 0.00076247496 -MAE (mean ABS error): 0.00048693258 -maxAE (max ABS error) 0.013423204 -Lipschitz bound: 9.7745784e7 +R² score: 0.9999991 +MSE (mean SQR error): 8.908188e-7 +RMSE (Root MSE): 0.00094383204 +MAE (mean ABS error): 0.00054397504 +maxAE (max ABS error) 0.028520107 +Lipschitz bound: 1.6673235e8 #======================# #======================# TEST STATS -R² score: 0.99999946 -MSE (mean SQR error): 5.8136806e-7 -RMSE (Root MSE): 0.00076247496 -MAE (mean ABS error): 0.00048693258 -maxAE (max ABS error) 0.013423204 -Lipschitz bound: 9.7745784e7 +R² score: 0.9999991 +MSE (mean SQR error): 8.908188e-7 +RMSE (Root MSE): 0.00094383204 +MAE (mean ABS error): 0.00054397504 +maxAE (max ABS error) 0.028520107 +Lipschitz bound: 1.6673235e8 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_07.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_07.txt index 215f5775..6ef719c2 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_07.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_07.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 1.774046e-6 || TEST LOSS: 1.7740458e-6 +Epoch [0 / 0] TRAIN LOSS: 2.3969992e-6 || TEST LOSS: 2.3969992e-6 #======================# TRAIN STATS -R² score: 0.9999996 -MSE (mean SQR error): 4.219962e-7 -RMSE (Root MSE): 0.00064961234 -MAE (mean ABS error): 0.00043178714 -maxAE (max ABS error) 0.009002686 -Lipschitz bound: 1.0472135e8 +R² score: 0.9999992 +MSE (mean SQR error): 7.828827e-7 +RMSE (Root MSE): 0.0008848067 +MAE (mean ABS error): 0.0005050862 +maxAE (max ABS error) 0.020621777 +Lipschitz bound: 1.9143933e8 #======================# #======================# TEST STATS -R² score: 0.9999996 -MSE (mean SQR error): 4.2199616e-7 -RMSE (Root MSE): 0.00064961234 -MAE (mean ABS error): 0.00043178708 -maxAE (max ABS error) 0.009002686 -Lipschitz bound: 1.0472135e8 +R² score: 0.9999992 +MSE (mean SQR error): 7.828827e-7 +RMSE (Root MSE): 0.0008848067 +MAE (mean ABS error): 0.0005050862 +maxAE (max ABS error) 0.020621777 +Lipschitz bound: 1.9143933e8 #======================# diff --git a/examples/ks_fourier/model_SNFW_l_16/statistics_08.txt b/examples/ks_fourier/model_SNFW_l_16/statistics_08.txt index 4a7f203a..caa806b5 100644 --- a/examples/ks_fourier/model_SNFW_l_16/statistics_08.txt +++ b/examples/ks_fourier/model_SNFW_l_16/statistics_08.txt @@ -1,21 +1,21 @@ -Epoch [0 / 0] TRAIN LOSS: 1.3946525e-6 || TEST LOSS: 1.3946525e-6 +Epoch [0 / 0] TRAIN LOSS: 1.5420014e-6 || TEST LOSS: 1.5420014e-6 #======================# TRAIN STATS -R² score: 0.9999997 -MSE (mean SQR error): 3.287307e-7 -RMSE (Root MSE): 0.0005733504 -MAE (mean ABS error): 0.00039350957 -maxAE (max ABS error) 0.009036064 -Lipschitz bound: 1.0908289e8 +R² score: 0.9999995 +MSE (mean SQR error): 4.9039807e-7 +RMSE (Root MSE): 0.00070028426 +MAE (mean ABS error): 0.00043297824 +maxAE (max ABS error) 0.011007071 +Lipschitz bound: 2.0775102e8 #======================# #======================# TEST STATS -R² score: 0.9999997 -MSE (mean SQR error): 3.2873075e-7 -RMSE (Root MSE): 0.00057335047 -MAE (mean ABS error): 0.0003935096 -maxAE (max ABS error) 0.009036064 -Lipschitz bound: 1.0908289e8 +R² score: 0.9999995 +MSE (mean SQR error): 4.9039807e-7 +RMSE (Root MSE): 0.00070028426 +MAE (mean ABS error): 0.00043297824 +maxAE (max ABS error) 0.011007071 +Lipschitz bound: 2.0775102e8 #======================#