AbstractPhil commited on
Commit
3b30195
Β·
verified Β·
1 Parent(s): d75a974

Freckles kept up without using hidden states. Next up, hidden states.

Browse files
Files changed (1) hide show
  1. omega_vs_baseline_output.txt +362 -0
omega_vs_baseline_output.txt ADDED
@@ -0,0 +1,362 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured.
2
+ WARNING:huggingface_hub._login:Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured.
3
+
4
+ ======================================================================
5
+ OMEGA PROCESSOR β€” CIFAR-10 (Freckles features)
6
+ ======================================================================
7
+ Freckles: 2,557,539 params (frozen)
8
+ Feature dim: 64
9
+ Classifier: 836,234 params
10
+ Architecture: d_model=128, heads=4, layers=4
11
+ CIFAR-10: 50K train, 10K test, 64Γ—64
12
+ Batch: 128, lr=0.0003, epochs=30
13
+ ======================================================================
14
+ 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 170M/170M [00:01<00:00, 91.1MB/s]
15
+ Ep 1/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:10<00:00, 38.21it/s, loss=1.8147 acc=23.6%]
16
+ ep 1 | loss=2.0322 train=23.6% test=33.4% | best=truck=70% worst=bird=1% | 12s
17
+
18
+ class acc
19
+ ----------------------
20
+ airplane 44.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
21
+ automobile 30.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
22
+ bird 1.5%
23
+ cat 22.7% β–ˆβ–ˆβ–ˆβ–ˆ
24
+ deer 10.3% β–ˆβ–ˆ
25
+ dog 34.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
26
+ frog 54.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
27
+ horse 36.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
28
+ ship 30.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
29
+ truck 69.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
30
+
31
+ Ep 2/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.18it/s, loss=1.6721 acc=38.5%]
32
+ ep 2 | loss=1.6980 train=38.5% test=44.8% | best=automobile=74% worst=cat=16% | 11s
33
+ Ep 3/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.22it/s, loss=1.4097 acc=45.5%]
34
+ ep 3 | loss=1.5104 train=45.5% test=49.5% | best=frog=70% worst=cat=25% | 11s
35
+ Ep 4/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.03it/s, loss=1.4453 acc=50.1%]
36
+ ep 4 | loss=1.3840 train=50.1% test=54.4% | best=ship=81% worst=cat=25% | 11s
37
+ Ep 5/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.01it/s, loss=1.0432 acc=54.3%]
38
+ ep 5 | loss=1.2717 train=54.3% test=56.5% | best=ship=80% worst=bird=37% | 11s
39
+
40
+ class acc
41
+ ----------------------
42
+ airplane 67.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
43
+ automobile 72.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
44
+ bird 36.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
45
+ cat 40.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
46
+ deer 57.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
47
+ dog 39.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
48
+ frog 72.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
49
+ horse 59.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
50
+ ship 80.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
51
+ truck 39.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
52
+
53
+ Ep 6/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:10<00:00, 38.27it/s, loss=1.1928 acc=57.3%]
54
+ ep 6 | loss=1.1949 train=57.3% test=59.5% | best=ship=81% worst=dog=44% | 11s
55
+ Ep 7/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.01it/s, loss=1.3602 acc=59.9%]
56
+ ep 7 | loss=1.1243 train=59.9% test=59.7% | best=truck=78% worst=cat=23% | 11s
57
+ Ep 8/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.22it/s, loss=1.2255 acc=61.8%]
58
+ ep 8 | loss=1.0698 train=61.8% test=62.1% | best=truck=74% worst=cat=44% | 11s
59
+ Ep 9/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:10<00:00, 38.57it/s, loss=1.2281 acc=63.4%]
60
+ ep 9 | loss=1.0276 train=63.4% test=64.0% | best=automobile=83% worst=cat=35% | 11s
61
+ Ep 10/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.23it/s, loss=0.9413 acc=64.9%]
62
+ ep 10 | loss=0.9864 train=64.9% test=65.4% | best=ship=81% worst=bird=46% | 11s
63
+
64
+ class acc
65
+ ----------------------
66
+ airplane 63.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
67
+ automobile 76.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
68
+ bird 46.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
69
+ cat 51.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
70
+ deer 60.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
71
+ dog 51.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
72
+ frog 73.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
73
+ horse 73.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
74
+ ship 81.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
75
+ truck 77.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
76
+
77
+ Ep 11/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.06it/s, loss=0.9747 acc=66.2%]
78
+ ep 11 | loss=0.9497 train=66.2% test=66.0% | best=truck=81% worst=bird=47% | 11s
79
+ Ep 12/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.04it/s, loss=0.9341 acc=67.2%]
80
+ ep 12 | loss=0.9211 train=67.2% test=65.3% | best=airplane=82% worst=cat=36% | 11s
81
+ Ep 13/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.17it/s, loss=1.0120 acc=68.2%]
82
+ ep 13 | loss=0.8938 train=68.2% test=67.7% | best=frog=84% worst=cat=44% | 11s
83
+ Ep 14/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.26it/s, loss=0.8321 acc=69.3%]
84
+ ep 14 | loss=0.8613 train=69.3% test=68.3% | best=automobile=83% worst=cat=50% | 11s
85
+ Ep 15/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.07it/s, loss=0.8031 acc=70.3%]
86
+ ep 15 | loss=0.8360 train=70.3% test=68.7% | best=automobile=81% worst=cat=39% | 11s
87
+
88
+ class acc
89
+ ----------------------
90
+ airplane 76.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
91
+ automobile 81.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
92
+ bird 52.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
93
+ cat 39.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
94
+ deer 67.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
95
+ dog 60.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
96
+ frog 76.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
97
+ horse 75.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
98
+ ship 78.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
99
+ truck 78.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
100
+
101
+ Ep 16/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.20it/s, loss=1.0140 acc=71.0%]
102
+ ep 16 | loss=0.8155 train=71.0% test=69.5% | best=frog=86% worst=cat=43% | 11s
103
+ Ep 17/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.14it/s, loss=0.6555 acc=72.0%]
104
+ ep 17 | loss=0.7903 train=72.0% test=69.3% | best=automobile=86% worst=cat=43% | 11s
105
+ Ep 18/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.01it/s, loss=0.6629 acc=72.9%]
106
+ ep 18 | loss=0.7687 train=72.9% test=70.1% | best=ship=84% worst=cat=53% | 11s
107
+ Ep 19/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.17it/s, loss=0.6098 acc=73.3%]
108
+ ep 19 | loss=0.7525 train=73.3% test=70.9% | best=automobile=82% worst=cat=47% | 11s
109
+ Ep 20/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:10<00:00, 38.60it/s, loss=0.6530 acc=74.3%]
110
+ ep 20 | loss=0.7280 train=74.3% test=71.1% | best=airplane=85% worst=cat=52% | 11s
111
+
112
+ class acc
113
+ ----------------------
114
+ airplane 84.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
115
+ automobile 82.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
116
+ bird 55.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
117
+ cat 52.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
118
+ deer 66.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
119
+ dog 59.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
120
+ frog 78.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
121
+ horse 73.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
122
+ ship 79.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
123
+ truck 78.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
124
+
125
+ Ep 21/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.05it/s, loss=0.7255 acc=74.7%]
126
+ ep 21 | loss=0.7183 train=74.7% test=70.8% | best=frog=89% worst=cat=52% | 11s
127
+ Ep 22/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.13it/s, loss=0.7117 acc=75.2%]
128
+ ep 22 | loss=0.7030 train=75.2% test=71.1% | best=automobile=87% worst=cat=49% | 11s
129
+ Ep 23/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.06it/s, loss=0.6705 acc=75.5%]
130
+ ep 23 | loss=0.6897 train=75.5% test=71.0% | best=truck=83% worst=cat=47% | 11s
131
+ Ep 24/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.19it/s, loss=0.6390 acc=76.0%]
132
+ ep 24 | loss=0.6786 train=76.0% test=72.0% | best=automobile=82% worst=cat=50% | 11s
133
+ Ep 25/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.14it/s, loss=0.5925 acc=76.5%]
134
+ ep 25 | loss=0.6657 train=76.5% test=72.0% | best=automobile=86% worst=cat=52% | 11s
135
+
136
+ class acc
137
+ ----------------------
138
+ airplane 81.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
139
+ automobile 86.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
140
+ bird 56.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
141
+ cat 52.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
142
+ deer 68.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
143
+ dog 58.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
144
+ frog 80.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
145
+ horse 76.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆοΏ½οΏ½β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
146
+ ship 80.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
147
+ truck 79.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
148
+
149
+ Ep 26/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.24it/s, loss=0.6332 acc=76.5%]
150
+ ep 26 | loss=0.6614 train=76.5% test=72.1% | best=frog=84% worst=cat=48% | 11s
151
+ Ep 27/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.14it/s, loss=0.6383 acc=76.9%]
152
+ ep 27 | loss=0.6535 train=76.9% test=72.2% | best=automobile=86% worst=cat=50% | 11s
153
+ Ep 28/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.15it/s, loss=0.7896 acc=77.2%]
154
+ ep 28 | loss=0.6451 train=77.2% test=72.6% | best=automobile=84% worst=cat=50% | 11s
155
+ Ep 29/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:09<00:00, 39.19it/s, loss=0.6121 acc=77.4%]
156
+ ep 29 | loss=0.6410 train=77.4% test=72.7% | best=automobile=84% worst=cat=51% | 11s
157
+ Ep 30/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:10<00:00, 38.99it/s, loss=0.7349 acc=77.5%]
158
+ ep 30 | loss=0.6390 train=77.5% test=72.7% | best=automobile=84% worst=cat=51% | 11s
159
+
160
+ class acc
161
+ ----------------------
162
+ airplane 79.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
163
+ automobile 83.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
164
+ bird 59.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
165
+ cat 50.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
166
+ deer 68.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
167
+ dog 63.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
168
+ frog 82.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
169
+ horse 76.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
170
+ ship 82.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
171
+ truck 80.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
172
+
173
+
174
+ ======================================================================
175
+ OMEGA PROCESSOR COMPLETE
176
+ Best test accuracy: 72.7%
177
+ Classifier params: 836,234
178
+ Random chance: 10.0%
179
+ ======================================================================
180
+
181
+ ======================================================================
182
+ BASELINE β€” CIFAR-10 (Raw patches, no Freckles)
183
+ ======================================================================
184
+ Classifier: 867,050 params
185
+ Architecture: d_model=128, heads=4, layers=4
186
+ CIFAR-10: 50K train, 10K test, 64Γ—64
187
+ Batch: 128, lr=0.0003, epochs=30
188
+ ======================================================================
189
+ Ep 1/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.28it/s, loss=1.6722 acc=32.2%]
190
+ ep 1 | loss=1.8088 train=32.2% test=42.3% | best=ship=62% worst=deer=18% | 6s
191
+
192
+ class acc
193
+ ----------------------
194
+ airplane 47.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
195
+ automobile 59.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
196
+ bird 32.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
197
+ cat 21.7% β–ˆβ–ˆβ–ˆβ–ˆ
198
+ deer 17.9% β–ˆβ–ˆβ–ˆ
199
+ dog 32.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
200
+ frog 61.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
201
+ horse 41.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
202
+ ship 62.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
203
+ truck 46.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
204
+
205
+ Ep 2/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.53it/s, loss=1.3286 acc=46.4%]
206
+ ep 2 | loss=1.4489 train=46.4% test=51.9% | best=frog=66% worst=cat=20% | 6s
207
+ Ep 3/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.29it/s, loss=1.2655 acc=53.2%]
208
+ ep 3 | loss=1.2781 train=53.2% test=56.3% | best=ship=75% worst=cat=28% | 6s
209
+ Ep 4/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.42it/s, loss=1.1440 acc=57.9%]
210
+ ep 4 | loss=1.1618 train=57.9% test=60.5% | best=frog=82% worst=bird=34% | 6s
211
+ Ep 5/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:06<00:00, 64.95it/s, loss=1.1496 acc=61.4%]
212
+ ep 5 | loss=1.0723 train=61.4% test=63.2% | best=horse=79% worst=cat=31% | 6s
213
+
214
+ class acc
215
+ ----------------------
216
+ airplane 69.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
217
+ automobile 76.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
218
+ bird 38.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
219
+ cat 30.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
220
+ deer 56.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
221
+ dog 62.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
222
+ frog 72.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
223
+ horse 78.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
224
+ ship 74.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
225
+ truck 72.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
226
+
227
+ Ep 6/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.25it/s, loss=0.8846 acc=64.0%]
228
+ ep 6 | loss=1.0052 train=64.0% test=62.7% | best=frog=89% worst=bird=32% | 6s
229
+ Ep 7/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.29it/s, loss=0.9618 acc=66.5%]
230
+ ep 7 | loss=0.9418 train=66.5% test=65.2% | best=truck=87% worst=cat=32% | 6s
231
+ Ep 8/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.03it/s, loss=0.9562 acc=68.3%]
232
+ ep 8 | loss=0.8913 train=68.3% test=68.0% | best=ship=87% worst=cat=45% | 6s
233
+ Ep 9/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.12it/s, loss=0.8684 acc=69.9%]
234
+ ep 9 | loss=0.8519 train=69.9% test=68.6% | best=truck=85% worst=cat=40% | 6s
235
+ Ep 10/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.12it/s, loss=0.6724 acc=71.3%]
236
+ ep 10 | loss=0.8107 train=71.3% test=68.6% | best=ship=84% worst=dog=46% | 6s
237
+
238
+ class acc
239
+ ----------------------
240
+ airplane 76.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
241
+ automobile 64.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
242
+ bird 53.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
243
+ cat 54.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
244
+ deer 72.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
245
+ dog 45.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
246
+ frog 78.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
247
+ horse 76.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
248
+ ship 84.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
249
+ truck 78.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
250
+
251
+ Ep 11/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.00it/s, loss=0.7053 acc=72.5%]
252
+ ep 11 | loss=0.7744 train=72.5% test=71.5% | best=automobile=85% worst=cat=47% | 6s
253
+ Ep 12/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.48it/s, loss=0.7007 acc=73.8%]
254
+ ep 12 | loss=0.7421 train=73.8% test=71.8% | best=truck=88% worst=cat=50% | 6s
255
+ Ep 13/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:06<00:00, 64.77it/s, loss=0.6695 acc=74.9%]
256
+ ep 13 | loss=0.7130 train=74.9% test=72.3% | best=automobile=90% worst=cat=49% | 6s
257
+ Ep 14/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:06<00:00, 64.57it/s, loss=0.6952 acc=75.6%]
258
+ ep 14 | loss=0.6917 train=75.6% test=72.6% | best=automobile=90% worst=dog=48% | 6s
259
+ Ep 15/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.06it/s, loss=0.5546 acc=76.7%]
260
+ ep 15 | loss=0.6617 train=76.7% test=73.7% | best=automobile=91% worst=dog=60% | 6s
261
+
262
+ class acc
263
+ ----------------------
264
+ airplane 80.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
265
+ automobile 91.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
266
+ bird 68.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
267
+ cat 60.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
268
+ deer 66.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
269
+ dog 60.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
270
+ frog 79.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
271
+ horse 76.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
272
+ ship 85.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
273
+ truck 70.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
274
+
275
+ Ep 16/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.05it/s, loss=0.6078 acc=77.6%]
276
+ ep 16 | loss=0.6364 train=77.6% test=74.0% | best=automobile=88% worst=cat=55% | 6s
277
+ Ep 17/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.26it/s, loss=0.7195 acc=78.4%]
278
+ ep 17 | loss=0.6122 train=78.4% test=74.8% | best=automobile=89% worst=cat=60% | 6s
279
+ Ep 18/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.46it/s, loss=0.5613 acc=79.2%]
280
+ ep 18 | loss=0.5941 train=79.2% test=75.1% | best=automobile=90% worst=cat=57% | 6s
281
+ Ep 19/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.23it/s, loss=0.4989 acc=79.7%]
282
+ ep 19 | loss=0.5762 train=79.7% test=75.1% | best=automobile=90% worst=cat=60% | 6s
283
+ Ep 20/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.22it/s, loss=0.6564 acc=80.5%]
284
+ ep 20 | loss=0.5553 train=80.5% test=75.8% | best=automobile=87% worst=bird=60% | 6s
285
+
286
+ class acc
287
+ ----------------------
288
+ airplane 81.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
289
+ automobile 87.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
290
+ bird 59.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
291
+ cat 62.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
292
+ deer 71.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
293
+ dog 63.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
294
+ frog 85.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
295
+ horse 79.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
296
+ ship 85.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
297
+ truck 82.6% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
298
+
299
+ Ep 21/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.23it/s, loss=0.5616 acc=81.1%]
300
+ ep 21 | loss=0.5364 train=81.1% test=75.2% | best=truck=88% worst=cat=53% | 6s
301
+ Ep 22/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.54it/s, loss=0.4172 acc=81.8%]
302
+ ep 22 | loss=0.5201 train=81.8% test=76.4% | best=automobile=88% worst=cat=56% | 6s
303
+ Ep 23/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:06<00:00, 64.75it/s, loss=0.6296 acc=82.2%]
304
+ ep 23 | loss=0.5099 train=82.2% test=76.2% | best=automobile=88% worst=cat=65% | 6s
305
+ Ep 24/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:06<00:00, 64.50it/s, loss=0.4983 acc=82.9%]
306
+ ep 24 | loss=0.4906 train=82.9% test=76.4% | best=ship=87% worst=cat=60% | 6s
307
+ Ep 25/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.10it/s, loss=0.5062 acc=83.0%]
308
+ ep 25 | loss=0.4863 train=83.0% test=76.6% | best=automobile=89% worst=cat=56% | 6s
309
+
310
+ class acc
311
+ ----------------------
312
+ airplane 80.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
313
+ automobile 89.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
314
+ bird 62.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
315
+ cat 55.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
316
+ deer 73.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
317
+ dog 71.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
318
+ frog 86.9% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
319
+ horse 78.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
320
+ ship 83.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
321
+ truck 84.0% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
322
+
323
+ Ep 26/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.21it/s, loss=0.4450 acc=83.4%]
324
+ ep 26 | loss=0.4762 train=83.4% test=77.0% | best=truck=87% worst=cat=58% | 6s
325
+ Ep 27/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.23it/s, loss=0.5349 acc=83.5%]
326
+ ep 27 | loss=0.4720 train=83.5% test=77.2% | best=automobile=87% worst=cat=59% | 6s
327
+ Ep 28/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.20it/s, loss=0.4860 acc=83.8%]
328
+ ep 28 | loss=0.4634 train=83.8% test=76.9% | best=automobile=87% worst=cat=59% | 6s
329
+ Ep 29/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.58it/s, loss=0.3822 acc=84.0%]
330
+ ep 29 | loss=0.4596 train=84.0% test=77.0% | best=automobile=88% worst=cat=59% | 6s
331
+ Ep 30/30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 390/390 [00:05<00:00, 65.01it/s, loss=0.3785 acc=84.1%]
332
+ ep 30 | loss=0.4574 train=84.1% test=77.1% | best=automobile=87% worst=cat=59% | 6s
333
+
334
+ class acc
335
+ ----------------------
336
+ airplane 79.7% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
337
+ automobile 87.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
338
+ bird 65.3% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
339
+ cat 58.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
340
+ deer 74.4% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
341
+ dog 70.8% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
342
+ frog 84.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
343
+ horse 80.2% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
344
+ ship 84.5% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
345
+ truck 86.1% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ
346
+
347
+
348
+ ======================================================================
349
+ BASELINE COMPLETE
350
+ Best test accuracy: 77.2%
351
+ Classifier params: 867,050
352
+ Random chance: 10.0%
353
+ ======================================================================
354
+
355
+ ======================================================================
356
+ HEAD-TO-HEAD COMPARISON
357
+ ======================================================================
358
+ Omega Processor (Freckles features): 72.7%
359
+ Baseline (raw patches): 77.2%
360
+ Delta: -4.5%
361
+ Random chance: 10.0%
362
+ ======================================================================