[[ 0. 0. 5. ..., 0. 0. 0.]
[ 0. 0. 0. ..., 10. 0. 0.]
[ 0. 0. 0. ..., 16. 9. 0.]
...,
[ 0. 0. 1. ..., 6. 0. 0.]
[ 0. 0. 2. ..., 12. 0. 0.]
[ 0. 0. 10. ..., 12. 1. 0.]]
[0 1 2 ..., 8 9 8]
89 - 1708
Iteration 1, loss = 2.46768885
Iteration 2, loss = 2.38033061
Iteration 3, loss = 2.29925152
Iteration 4, loss = 2.22463505
Iteration 5, loss = 2.15647782
Iteration 6, loss = 2.09454238
Iteration 7, loss = 2.03839964
Iteration 8, loss = 1.98747972
Iteration 9, loss = 1.94110395
Iteration 10, loss = 1.89852225
Iteration 11, loss = 1.85896302
Iteration 12, loss = 1.82168707
Iteration 13, loss = 1.78604975
Iteration 14, loss = 1.75155875
Iteration 15, loss = 1.71790101
Iteration 16, loss = 1.68492708
Iteration 17, loss = 1.65259757
Iteration 18, loss = 1.62091573
Iteration 19, loss = 1.58987432
Iteration 20, loss = 1.55942859
Iteration 21, loss = 1.52949835
Iteration 22, loss = 1.49998760
Iteration 23, loss = 1.47080368
Iteration 24, loss = 1.44186863
Iteration 25, loss = 1.41312518
Iteration 26, loss = 1.38454126
Iteration 27, loss = 1.35611230
Iteration 28, loss = 1.32786010
Iteration 29, loss = 1.29982788
Iteration 30, loss = 1.27207182
Iteration 31, loss = 1.24465132
Iteration 32, loss = 1.21762116
Iteration 33, loss = 1.19102777
Iteration 34, loss = 1.16490892
Iteration 35, loss = 1.13929308
Iteration 36, loss = 1.11419478
Iteration 37, loss = 1.08960623
Iteration 38, loss = 1.06549435
Iteration 39, loss = 1.04181462
Iteration 40, loss = 1.01853284
Iteration 41, loss = 0.99563432
Iteration 42, loss = 0.97312009
Iteration 43, loss = 0.95099612
Iteration 44, loss = 0.92926375
Iteration 45, loss = 0.90792036
Iteration 46, loss = 0.88696610
Iteration 47, loss = 0.86640611
Iteration 48, loss = 0.84624805
Iteration 49, loss = 0.82649804
Iteration 50, loss = 0.80715832
Iteration 51, loss = 0.78822799
Iteration 52, loss = 0.76970567
Iteration 53, loss = 0.75159177
Iteration 54, loss = 0.73388877
Iteration 55, loss = 0.71659903
Iteration 56, loss = 0.69972145
Iteration 57, loss = 0.68324885
Iteration 58, loss = 0.66716787
Iteration 59, loss = 0.65146133
Iteration 60, loss = 0.63611161
Iteration 61, loss = 0.62110117
Iteration 62, loss = 0.60640861
Iteration 63, loss = 0.59200500
Iteration 64, loss = 0.57786082
Iteration 65, loss = 0.56396033
Iteration 66, loss = 0.55031006
Iteration 67, loss = 0.53693942
Iteration 68, loss = 0.52389273
Iteration 69, loss = 0.51121012
Iteration 70, loss = 0.49890376
Iteration 71, loss = 0.48695067
Iteration 72, loss = 0.47531389
Iteration 73, loss = 0.46396803
Iteration 74, loss = 0.45290618
Iteration 75, loss = 0.44213369
Iteration 76, loss = 0.43165960
Iteration 77, loss = 0.42148932
Iteration 78, loss = 0.41161996
Iteration 79, loss = 0.40203944
Iteration 80, loss = 0.39272991
Iteration 81, loss = 0.38367336
Iteration 82, loss = 0.37485611
Iteration 83, loss = 0.36627029
Iteration 84, loss = 0.35791258
Iteration 85, loss = 0.34978175
Iteration 86, loss = 0.34187631
Iteration 87, loss = 0.33419296
Iteration 88, loss = 0.32672614
Iteration 89, loss = 0.31946839
Iteration 90, loss = 0.31241133
Iteration 91, loss = 0.30554669
Iteration 92, loss = 0.29886713
Iteration 93, loss = 0.29236656
Iteration 94, loss = 0.28603999
Iteration 95, loss = 0.27988317
Iteration 96, loss = 0.27389213
Iteration 97, loss = 0.26806282
Iteration 98, loss = 0.26239092
Iteration 99, loss = 0.25687185
Iteration 100, loss = 0.25150087
Iteration 101, loss = 0.24627321
Iteration 102, loss = 0.24118429
Iteration 103, loss = 0.23622975
Iteration 104, loss = 0.23140557
Iteration 105, loss = 0.22670804
Iteration 106, loss = 0.22213369
Iteration 107, loss = 0.21767928
Iteration 108, loss = 0.21334167
Iteration 109, loss = 0.20911782
Iteration 110, loss = 0.20500464
Iteration 111, loss = 0.20099910
Iteration 112, loss = 0.19709814
Iteration 113, loss = 0.19329876
Iteration 114, loss = 0.18959805
Iteration 115, loss = 0.18599320
Iteration 116, loss = 0.18248150
Iteration 117, loss = 0.17906033
Iteration 118, loss = 0.17572716
Iteration 119, loss = 0.17247946
Iteration 120, loss = 0.16931476
Iteration 121, loss = 0.16623060
Iteration 122, loss = 0.16322456
Iteration 123, loss = 0.16029429
Iteration 124, loss = 0.15743753
Iteration 125, loss = 0.15465213
Iteration 126, loss = 0.15193604
Iteration 127, loss = 0.14928734
Iteration 128, loss = 0.14670421
Iteration 129, loss = 0.14418492
Iteration 130, loss = 0.14172781
Iteration 131, loss = 0.13933125
Iteration 132, loss = 0.13699364
Iteration 133, loss = 0.13471337
Iteration 134, loss = 0.13248887
Iteration 135, loss = 0.13031856
Iteration 136, loss = 0.12820086
Iteration 137, loss = 0.12613427
Iteration 138, loss = 0.12411730
Iteration 139, loss = 0.12214851
Iteration 140, loss = 0.12022653
Iteration 141, loss = 0.11835002
Iteration 142, loss = 0.11651767
Iteration 143, loss = 0.11472821
Iteration 144, loss = 0.11298040
Iteration 145, loss = 0.11127304
Iteration 146, loss = 0.10960493
Iteration 147, loss = 0.10797492
Iteration 148, loss = 0.10638190
Iteration 149, loss = 0.10482478
Iteration 150, loss = 0.10330252
Iteration 151, loss = 0.10181412
Iteration 152, loss = 0.10035860
Iteration 153, loss = 0.09893503
Iteration 154, loss = 0.09754252
Iteration 155, loss = 0.09618018
Iteration 156, loss = 0.09484719
Iteration 157, loss = 0.09354270
Iteration 158, loss = 0.09226595
Iteration 159, loss = 0.09101614
Iteration 160, loss = 0.08979255
Iteration 161, loss = 0.08859444
Iteration 162, loss = 0.08742113
Iteration 163, loss = 0.08627194
Iteration 164, loss = 0.08514621
Iteration 165, loss = 0.08404332
Iteration 166, loss = 0.08296266
Iteration 167, loss = 0.08190364
Iteration 168, loss = 0.08086568
Iteration 169, loss = 0.07984823
Iteration 170, loss = 0.07885075
Iteration 171, loss = 0.07787273
Iteration 172, loss = 0.07691366
Iteration 173, loss = 0.07597306
Iteration 174, loss = 0.07505045
Iteration 175, loss = 0.07414538
Iteration 176, loss = 0.07325740
Iteration 177, loss = 0.07238609
Iteration 178, loss = 0.07153102
Iteration 179, loss = 0.07069180
Iteration 180, loss = 0.06986804
Iteration 181, loss = 0.06905936
Iteration 182, loss = 0.06826538
Iteration 183, loss = 0.06748575
Iteration 184, loss = 0.06672014
Iteration 185, loss = 0.06596819
Iteration 186, loss = 0.06522959
Iteration 187, loss = 0.06450402
Iteration 188, loss = 0.06379117
Iteration 189, loss = 0.06309074
Iteration 190, loss = 0.06240244
Iteration 191, loss = 0.06172600
Iteration 192, loss = 0.06106113
Iteration 193, loss = 0.06040757
Iteration 194, loss = 0.05976506
Iteration 195, loss = 0.05913335
Iteration 196, loss = 0.05851220
Iteration 197, loss = 0.05790136
Iteration 198, loss = 0.05730061
Iteration 199, loss = 0.05670972
Iteration 200, loss = 0.05612846
precision recall f1-score support
0 0.99 0.98 0.99 170
1 0.68 0.88 0.77 172
2 0.97 0.76 0.85 172
3 0.97 0.86 0.91 177
4 0.98 0.72 0.83 176
5 0.94 0.94 0.94 168
6 0.96 0.97 0.97 170
7 0.93 0.91 0.92 173
8 0.76 0.74 0.75 164
9 0.72 0.97 0.83 166
avg / total 0.89 0.87 0.88 1708