Freckles kept up without using hidden states. Next up, hidden states.
Browse files- omega_vs_baseline_output.txt +362 -0
omega_vs_baseline_output.txt
ADDED
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| 1 |
+
Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured.
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| 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, 64Γ64
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| 12 |
+
Batch: 128, lr=0.0003, epochs=30
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| 13 |
+
======================================================================
|
| 14 |
+
100%|ββββββββββ| 170M/170M [00:01<00:00, 91.1MB/s]
|
| 15 |
+
Ep 1/30: 100%|ββββββββββββββββββββ| 390/390 [00:10<00:00, 38.21it/s, loss=1.8147 acc=23.6%]
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| 16 |
+
ep 1 | loss=2.0322 train=23.6% test=33.4% | best=truck=70% worst=bird=1% | 12s
|
| 17 |
+
|
| 18 |
+
class acc
|
| 19 |
+
----------------------
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| 20 |
+
airplane 44.1% ββββββββ
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| 21 |
+
automobile 30.2% ββββββ
|
| 22 |
+
bird 1.5%
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| 23 |
+
cat 22.7% ββββ
|
| 24 |
+
deer 10.3% ββ
|
| 25 |
+
dog 34.8% ββββββ
|
| 26 |
+
frog 54.1% ββββββββββ
|
| 27 |
+
horse 36.4% βββββββ
|
| 28 |
+
ship 30.6% ββββββ
|
| 29 |
+
truck 69.7% βββββββββββββ
|
| 30 |
+
|
| 31 |
+
Ep 2/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 390/390 [00:09<00:00, 39.22it/s, loss=1.4097 acc=45.5%]
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| 34 |
+
ep 3 | loss=1.5104 train=45.5% test=49.5% | best=frog=70% worst=cat=25% | 11s
|
| 35 |
+
Ep 4/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% βββββββββββββ
|
| 43 |
+
automobile 72.4% ββββββββββββββ
|
| 44 |
+
bird 36.7% βββββββ
|
| 45 |
+
cat 40.3% ββββββββ
|
| 46 |
+
deer 57.8% βββββββββββ
|
| 47 |
+
dog 39.3% βββββββ
|
| 48 |
+
frog 72.9% ββββββββββββββ
|
| 49 |
+
horse 59.3% βββββββββββ
|
| 50 |
+
ship 80.0% ββββββββββββββββ
|
| 51 |
+
truck 39.3% βββββββ
|
| 52 |
+
|
| 53 |
+
Ep 6/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% ββββββββββββ
|
| 67 |
+
automobile 76.2% βββββββββββββββ
|
| 68 |
+
bird 46.0% βββββββββ
|
| 69 |
+
cat 51.0% ββββββββββ
|
| 70 |
+
deer 60.8% ββββββββββββ
|
| 71 |
+
dog 51.8% ββββββββββ
|
| 72 |
+
frog 73.0% ββββββββββββββ
|
| 73 |
+
horse 73.2% ββββββββββββββ
|
| 74 |
+
ship 81.5% ββββββββββββββββ
|
| 75 |
+
truck 77.1% βββββββββββββββ
|
| 76 |
+
|
| 77 |
+
Ep 11/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% βββββββββββββββ
|
| 91 |
+
automobile 81.1% ββββββββββββββββ
|
| 92 |
+
bird 52.9% ββββββββββ
|
| 93 |
+
cat 39.1% βββββββ
|
| 94 |
+
deer 67.7% βββββββββββββ
|
| 95 |
+
dog 60.5% ββββββββββββ
|
| 96 |
+
frog 76.6% βββββββββββββββ
|
| 97 |
+
horse 75.8% βββββββββββββββ
|
| 98 |
+
ship 78.3% βββββββββββββββ
|
| 99 |
+
truck 78.7% βββββββββββββββ
|
| 100 |
+
|
| 101 |
+
Ep 16/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% ββββββββββββββββ
|
| 115 |
+
automobile 82.0% ββββββββββββββββ
|
| 116 |
+
bird 55.6% βββββββββββ
|
| 117 |
+
cat 52.3% ββββββββββ
|
| 118 |
+
deer 66.9% βββββββββββββ
|
| 119 |
+
dog 59.3% βββββββββββ
|
| 120 |
+
frog 78.5% βββββββββββββββ
|
| 121 |
+
horse 73.4% ββββββββββββββ
|
| 122 |
+
ship 79.5% βββββββββββββββ
|
| 123 |
+
truck 78.3% βββββββββββββββ
|
| 124 |
+
|
| 125 |
+
Ep 21/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% ββββββββββββββββ
|
| 139 |
+
automobile 86.2% βββββββββββββββββ
|
| 140 |
+
bird 56.9% βββββββββββ
|
| 141 |
+
cat 52.5% ββββββββββ
|
| 142 |
+
deer 68.3% βββββββββββββ
|
| 143 |
+
dog 58.5% βββββββββββ
|
| 144 |
+
frog 80.0% ββββββββββββββββ
|
| 145 |
+
horse 76.0% ββββββοΏ½οΏ½ββββββββ
|
| 146 |
+
ship 80.9% ββββββββββββββββ
|
| 147 |
+
truck 79.1% βββββββββββββββ
|
| 148 |
+
|
| 149 |
+
Ep 26/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% βββββββββββββββ
|
| 163 |
+
automobile 83.8% ββββββββββββββββ
|
| 164 |
+
bird 59.8% βββββββββββ
|
| 165 |
+
cat 50.9% ββββββββββ
|
| 166 |
+
deer 68.4% βββββββββββββ
|
| 167 |
+
dog 63.1% ββββββββββββ
|
| 168 |
+
frog 82.0% ββββββββββββββββ
|
| 169 |
+
horse 76.9% βββββββββββββββ
|
| 170 |
+
ship 82.2% ββββββββββββββββ
|
| 171 |
+
truck 80.6% ββββββββββββββββ
|
| 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, 64Γ64
|
| 187 |
+
Batch: 128, lr=0.0003, epochs=30
|
| 188 |
+
======================================================================
|
| 189 |
+
Ep 1/30: 100%|ββββββββββββββββββββ| 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% βββββββββ
|
| 195 |
+
automobile 59.5% βββββββββββ
|
| 196 |
+
bird 32.3% ββββββ
|
| 197 |
+
cat 21.7% ββββ
|
| 198 |
+
deer 17.9% βββ
|
| 199 |
+
dog 32.4% ββββββ
|
| 200 |
+
frog 61.7% ββββββββββββ
|
| 201 |
+
horse 41.3% ββββββββ
|
| 202 |
+
ship 62.4% ββββββββββββ
|
| 203 |
+
truck 46.5% βββββββββ
|
| 204 |
+
|
| 205 |
+
Ep 2/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% βββββββββββββ
|
| 217 |
+
automobile 76.8% βββββββββββββββ
|
| 218 |
+
bird 38.6% βββββββ
|
| 219 |
+
cat 30.7% ββββββ
|
| 220 |
+
deer 56.0% βββββββββββ
|
| 221 |
+
dog 62.7% ββββββββββββ
|
| 222 |
+
frog 72.4% ββββββββββββββ
|
| 223 |
+
horse 78.7% βββββββββββββββ
|
| 224 |
+
ship 74.0% ββββββββββββββ
|
| 225 |
+
truck 72.2% ββββββββββββββ
|
| 226 |
+
|
| 227 |
+
Ep 6/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% βββββββββββββββ
|
| 241 |
+
automobile 64.8% ββββββββββββ
|
| 242 |
+
bird 53.8% ββββββββββ
|
| 243 |
+
cat 54.7% ββββββββββ
|
| 244 |
+
deer 72.6% ββββββββββββββ
|
| 245 |
+
dog 45.9% βββββββββ
|
| 246 |
+
frog 78.4% βββββββββββββββ
|
| 247 |
+
horse 76.2% βββββββββββββββ
|
| 248 |
+
ship 84.2% ββββββββββββββββ
|
| 249 |
+
truck 78.7% βββββββββββββββ
|
| 250 |
+
|
| 251 |
+
Ep 11/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% ββββββββββββββββ
|
| 265 |
+
automobile 91.3% ββββββββββββββββββ
|
| 266 |
+
bird 68.1% βββββββββββββ
|
| 267 |
+
cat 60.3% ββββββββββββ
|
| 268 |
+
deer 66.4% βββββββββββββ
|
| 269 |
+
dog 60.0% ββββββββββββ
|
| 270 |
+
frog 79.0% βββββββββββββββ
|
| 271 |
+
horse 76.0% βββββββββββββββ
|
| 272 |
+
ship 85.4% βββββββββββββββββ
|
| 273 |
+
truck 70.2% ββββββββββββββ
|
| 274 |
+
|
| 275 |
+
Ep 16/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% ββββββββββββββββ
|
| 289 |
+
automobile 87.0% βββββββββββββββββ
|
| 290 |
+
bird 59.8% βββββββββββ
|
| 291 |
+
cat 62.9% ββββββββββββ
|
| 292 |
+
deer 71.4% ββββββββββββββ
|
| 293 |
+
dog 63.7% ββββββββββββ
|
| 294 |
+
frog 85.0% βββββββββββββββββ
|
| 295 |
+
horse 79.0% βββββββββββββββ
|
| 296 |
+
ship 85.2% βββββββββββββββββ
|
| 297 |
+
truck 82.6% ββββββββββββββββ
|
| 298 |
+
|
| 299 |
+
Ep 21/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% ββββββββββββββββ
|
| 313 |
+
automobile 89.4% βββββββββββββββββ
|
| 314 |
+
bird 62.5% ββββββββββββ
|
| 315 |
+
cat 55.9% βββββββββββ
|
| 316 |
+
deer 73.8% ββββββββββββββ
|
| 317 |
+
dog 71.9% ββββββββββββββ
|
| 318 |
+
frog 86.9% βββββββββββββββββ
|
| 319 |
+
horse 78.0% βββββββββββββββ
|
| 320 |
+
ship 83.2% ββββββββββββββββ
|
| 321 |
+
truck 84.0% ββββββββββββββββ
|
| 322 |
+
|
| 323 |
+
Ep 26/30: 100%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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%|ββββββββββββββββββββ| 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% βββββββββββββββ
|
| 337 |
+
automobile 87.2% βββββββββββββββββ
|
| 338 |
+
bird 65.3% βββββββββββββ
|
| 339 |
+
cat 58.8% βββββββββββ
|
| 340 |
+
deer 74.4% ββββββββββββββ
|
| 341 |
+
dog 70.8% ββββββββββββββ
|
| 342 |
+
frog 84.1% ββββββββββββββββ
|
| 343 |
+
horse 80.2% ββββββββββββββββ
|
| 344 |
+
ship 84.5% ββββββββββββββββ
|
| 345 |
+
truck 86.1% βββββββββββββββββ
|
| 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 |
+
======================================================================
|