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Training from Scratch

Xitong Gao edited this page Jun 15, 2018 · 1 revision

Cifar-10 Classification with >90% Accuracy

Info

+-------------------------------------+-------------------+-----------+                                                             
| trainable                           | shape             | count     |
+-------------------------------------+-------------------+-----------+
| cifarnet_v3/conv0/weights:0         | 3 x 3 x 3 x 64    |     1,728 |
| cifarnet_v3/conv0/BatchNorm/gamma:0 | 64                |        64 |
| cifarnet_v3/conv0/BatchNorm/beta:0  | 64                |        64 |
| cifarnet_v3/conv1/weights:0         | 3 x 3 x 64 x 64   |    36,864 |
| cifarnet_v3/conv1/BatchNorm/gamma:0 | 64                |        64 |
| cifarnet_v3/conv1/BatchNorm/beta:0  | 64                |        64 |
| cifarnet_v3/conv2/weights:0         | 3 x 3 x 64 x 128  |    73,728 |
| cifarnet_v3/conv2/BatchNorm/gamma:0 | 128               |       128 |
| cifarnet_v3/conv2/BatchNorm/beta:0  | 128               |       128 |
| cifarnet_v3/conv3/weights:0         | 3 x 3 x 128 x 128 |   147,456 |
| cifarnet_v3/conv3/BatchNorm/gamma:0 | 128               |       128 |
| cifarnet_v3/conv3/BatchNorm/beta:0  | 128               |       128 |
| cifarnet_v3/conv4/weights:0         | 3 x 3 x 128 x 128 |   147,456 |
| cifarnet_v3/conv4/BatchNorm/gamma:0 | 128               |       128 |
| cifarnet_v3/conv4/BatchNorm/beta:0  | 128               |       128 |
| cifarnet_v3/conv5/weights:0         | 3 x 3 x 128 x 192 |   221,184 |
| cifarnet_v3/conv5/BatchNorm/gamma:0 | 192               |       192 |
| cifarnet_v3/conv5/BatchNorm/beta:0  | 192               |       192 |
| cifarnet_v3/conv6/weights:0         | 3 x 3 x 192 x 192 |   331,776 |
| cifarnet_v3/conv6/BatchNorm/gamma:0 | 192               |       192 |
| cifarnet_v3/conv6/BatchNorm/beta:0  | 192               |       192 |
| cifarnet_v3/conv7/weights:0         | 3 x 3 x 192 x 192 |   331,776 |
| cifarnet_v3/conv7/BatchNorm/gamma:0 | 192               |       192 |
| cifarnet_v3/conv7/BatchNorm/beta:0  | 192               |       192 |
| cifarnet_v3/logits/weights:0        | 1 x 1 x 192 x 10  |     1,920 |
| cifarnet_v3/logits/biases:0         | 10                |        10 |
+-------------------------------------+-------------------+-----------+
|                                     |     total:        | 1,296,074 |
+-------------------------------------+-------------------+-----------+
+----------------------+----------------------+
| layer                | shape                |
+----------------------+----------------------+
| cifarnet_v3/conv0    | 1024 x 30 x 30 x 64  |
| cifarnet_v3/conv1    | 1024 x 30 x 30 x 64  |
| cifarnet_v3/conv2    | 1024 x 15 x 15 x 128 |
| cifarnet_v3/conv3    | 1024 x 15 x 15 x 128 |
| cifarnet_v3/dropout3 | 1024 x 15 x 15 x 128 |
| cifarnet_v3/conv4    | 1024 x 15 x 15 x 128 |
| cifarnet_v3/conv5    | 1024 x 8 x 8 x 192   |
| cifarnet_v3/conv6    | 1024 x 8 x 8 x 192   |
| cifarnet_v3/dropout6 | 1024 x 8 x 8 x 192   |
| cifarnet_v3/conv7    | 1024 x 8 x 8 x 192   |
| cifarnet_v3/pool7    | 1024 x 1 x 1 x 192   |
| cifarnet_v3/logits   | 1024 x 1 x 1 x 10    |
| cifarnet_v3/squeeze  | 1024 x 10            |
+----------------------+----------------------+

Model YAML

---
dataset:
    background_class: {use: false}
    preprocess:
        shape:
            height: 32
            width: 32
            channels: 3
        validate:
            - {type: crop_or_pad}
        final_cpu:
            - {type: standardize_image}
model:
    name: cifarnet_v3
    description: Cifar-10 classification with >90% accuracy.
    layers:
        _conv: &conv
            type: convolution
            padding: same
            kernel_size: 3
            weights_initializer:
                type: tensorflow.variance_scaling_initializer
            weights_regularizer:
                type: tensorflow.contrib.layers.l2_regularizer
                scale: 0.0001
            normalizer_fn:
                type: tensorflow.contrib.slim.batch_norm
                center: true
                scale: true
                decay: 0.9997
                epsilon: 0.001
        conv0: {<<: *conv, padding: valid, num_outputs: 64}
        conv1: {<<: *conv, num_outputs: 64}
        conv2: {<<: *conv, num_outputs: 128, stride: 2}
        conv3: {<<: *conv, num_outputs: 128}
        dropout3: {type: dropout, keep_prob: 0.5}
        conv4: {<<: *conv, num_outputs: 128}
        conv5: {<<: *conv, num_outputs: 192, stride: 2}
        conv6: {<<: *conv, num_outputs: 192}
        dropout6: {type: dropout, keep_prob: 0.5}
        conv7: {<<: *conv, num_outputs: 192}
        pool7: {type: average_pool, kernel_size: 8}
        logits:
            <<: *conv
            kernel_size: 1
            num_outputs: num_classes
            activation_fn: null
            normalizer_fn: null
        squeeze: {type: squeeze, axis: [1, 2]}
    graph:
        from: input
        with: [
            conv0, conv1, conv2, conv3, dropout3,
            conv4, conv5, conv6, dropout6,
            conv7, pool7, logits, squeeze]
        to: output

Results

+---------+--------+--------+
| Epoch   | Top 1  | Top 5  |
+---------+--------+--------+
| 1.004   | 11.36% | 65.71% |
| 2.007   | 20.42% | 70.27% |
| 3.011   | 22.29% | 76.02% |
| 4.014   | 22.57% | 70.02% |
| 5.018   | 26.59% | 77.95% |
| 6.001   | 16.83% | 74.73% |
| 7.004   | 26.59% | 76.16% |
| 8.008   | 30.31% | 85.21% |
| 9.011   | 32.02% | 83.65% |
| 10.015  | 38.55% | 85.26% |
| 11.018  | 41.42% | 92.04% |
| 12.001  | 27.74% | 86.47% |
| 13.025  | 45.47% | 86.43% |
| 14.008  | 48.84% | 85.00% |
| 15.012  | 61.44% | 93.40% |
| 16.015  | 61.12% | 94.67% |
| 17.019  | 55.29% | 94.36% |
| 18.002  | 59.85% | 95.55% |
| 19.005  | 61.90% | 94.91% |
| 20.009  | 55.49% | 94.39% |
| 21.012  | 67.07% | 97.32% |
| 22.016  | 57.39% | 94.56% |
| 23.020  | 64.52% | 96.44% |
| 24.003  | 64.83% | 96.88% |
| 25.006  | 66.24% | 97.11% |
| 26.010  | 59.76% | 95.78% |
| 27.013  | 54.49% | 95.38% |
| 28.017  | 60.15% | 96.28% |
| 29.020  | 56.11% | 94.58% |
| 30.003  | 56.74% | 95.24% |
| 31.007  | 59.64% | 95.90% |
| 32.010  | 57.91% | 96.68% |
| 33.014  | 48.80% | 93.87% |
| 34.038  | 46.86% | 95.06% |
| 35.000  | 55.42% | 94.47% |
| 36.004  | 56.07% | 96.28% |
| 37.007  | 50.83% | 94.76% |
| 38.011  | 64.48% | 96.76% |
| 39.014  | 60.29% | 97.42% |
| 40.018  | 61.10% | 95.26% |
| 41.021  | 70.58% | 97.13% |
| 42.004  | 60.30% | 95.81% |
| 43.008  | 62.94% | 95.35% |
| 44.012  | 69.14% | 96.95% |
| 45.036  | 65.39% | 95.97% |
| 46.019  | 61.78% | 97.10% |
| 47.002  | 61.60% | 96.91% |
| 48.026  | 60.21% | 96.27% |
| 49.009  | 69.85% | 96.92% |
| 50.012  | 65.49% | 97.08% |
| 51.016  | 67.64% | 96.69% |
| 52.019  | 64.73% | 96.72% |
| 53.002  | 66.39% | 96.95% |
| 54.006  | 58.36% | 95.33% |
| 55.009  | 64.71% | 96.52% |
| 56.033  | 76.70% | 97.12% |
| 57.016  | 65.02% | 97.07% |
| 58.020  | 69.80% | 97.23% |
| 59.003  | 72.77% | 97.71% |
| 60.006  | 63.13% | 97.79% |
| 61.010  | 73.24% | 98.50% |
| 62.013  | 79.52% | 98.42% |
| 63.017  | 77.22% | 98.40% |
| 64.000  | 71.45% | 97.30% |
| 65.004  | 78.39% | 98.51% |
| 66.007  | 76.35% | 98.11% |
| 67.011  | 72.41% | 97.55% |
| 68.014  | 81.83% | 98.64% |
| 69.018  | 80.78% | 98.81% |
| 70.001  | 80.55% | 98.79% |
| 71.004  | 77.03% | 98.02% |
| 72.008  | 81.41% | 98.82% |
| 73.011  | 82.13% | 99.01% |
| 74.015  | 81.14% | 98.89% |
| 75.018  | 80.76% | 98.63% |
| 76.001  | 81.54% | 99.14% |
| 77.005  | 79.04% | 99.12% |
| 78.008  | 80.31% | 98.86% |
| 79.012  | 82.40% | 99.12% |
| 80.036  | 79.25% | 99.17% |
| 81.019  | 83.04% | 99.00% |
| 82.002  | 80.88% | 98.79% |
| 83.005  | 82.82% | 99.13% |
| 84.009  | 82.18% | 99.10% |
| 85.012  | 79.60% | 98.62% |
| 86.016  | 80.13% | 98.99% |
| 87.020  | 84.07% | 99.27% |
| 88.003  | 82.91% | 99.12% |
| 89.006  | 82.75% | 99.20% |
| 90.010  | 80.77% | 99.19% |
| 91.013  | 83.74% | 99.36% |
| 92.017  | 85.53% | 99.33% |
| 93.020  | 84.00% | 98.86% |
| 94.003  | 85.65% | 99.17% |
| 95.007  | 80.76% | 98.73% |
| 96.010  | 81.53% | 98.25% |
| 97.014  | 80.86% | 98.39% |
| 98.017  | 82.70% | 98.99% |
| 99.000  | 85.14% | 99.42% |
| 100.024 | 79.16% | 99.28% |
| 101.007 | 79.69% | 98.23% |
| 102.011 | 82.69% | 99.35% |
| 103.014 | 84.62% | 99.36% |
| 104.018 | 77.65% | 98.82% |
| 105.001 | 82.89% | 99.14% |
| 106.004 | 82.03% | 99.12% |
| 107.008 | 79.65% | 98.98% |
| 108.012 | 86.45% | 99.53% |
| 109.015 | 81.97% | 99.06% |
| 110.019 | 76.25% | 99.10% |
| 111.002 | 80.64% | 99.12% |
| 112.005 | 82.23% | 99.06% |
| 113.009 | 83.40% | 99.28% |
| 114.012 | 83.20% | 99.16% |
| 115.016 | 84.59% | 99.19% |
| 116.019 | 84.09% | 99.26% |
| 117.002 | 85.35% | 99.03% |
| 118.006 | 84.46% | 99.11% |
| 119.009 | 83.44% | 98.97% |
| 120.013 | 84.51% | 99.32% |
| 121.016 | 86.83% | 99.46% |
| 122.040 | 87.54% | 99.57% |
| 123.003 | 88.22% | 99.58% |
| 124.006 | 88.15% | 99.55% |
| 125.010 | 87.64% | 99.53% |
| 126.013 | 88.08% | 99.61% |
| 127.017 | 88.36% | 99.63% |
| 128.000 | 88.60% | 99.67% |
| 129.004 | 88.62% | 99.70% |
| 130.007 | 88.93% | 99.71% |
| 131.011 | 88.38% | 99.64% |
| 132.014 | 88.60% | 99.65% |
| 133.018 | 89.24% | 99.67% |
| 134.021 | 89.14% | 99.66% |
| 135.025 | 89.13% | 99.63% |
| 136.008 | 89.57% | 99.64% |
| 137.011 | 88.81% | 99.61% |
| 138.015 | 88.83% | 99.61% |
| 139.018 | 89.41% | 99.62% |
| 140.001 | 88.88% | 99.63% |
| 141.005 | 88.89% | 99.66% |
| 142.029 | 88.84% | 99.62% |
| 143.012 | 89.54% | 99.65% |
| 144.015 | 89.47% | 99.70% |
| 145.019 | 89.34% | 99.65% |
| 146.002 | 89.38% | 99.64% |
| 147.005 | 89.20% | 99.68% |
| 148.009 | 89.44% | 99.61% |
| 149.012 | 89.49% | 99.69% |
| 150.016 | 89.69% | 99.64% |
| 151.020 | 89.75% | 99.65% |
| 152.003 | 89.23% | 99.70% |
| 153.006 | 89.45% | 99.67% |
| 154.010 | 89.56% | 99.67% |
| 155.013 | 89.53% | 99.68% |
| 156.017 | 88.88% | 99.68% |
| 157.020 | 89.78% | 99.66% |
| 158.024 | 89.03% | 99.70% |
| 159.007 | 89.29% | 99.74% |
| 160.010 | 89.21% | 99.67% |
| 161.014 | 88.97% | 99.67% |
| 162.017 | 89.27% | 99.65% |
| 163.021 | 89.65% | 99.67% |
| 164.004 | 89.40% | 99.66% |
| 165.028 | 89.04% | 99.58% |
| 166.011 | 89.66% | 99.64% |
| 167.014 | 89.63% | 99.58% |
| 168.018 | 89.15% | 99.60% |
| 169.001 | 89.20% | 99.65% |
| 170.004 | 89.31% | 99.62% |
| 171.008 | 89.44% | 99.59% |
| 172.012 | 89.25% | 99.63% |
| 173.015 | 88.80% | 99.63% |
| 174.019 | 88.65% | 99.62% |
| 175.002 | 88.65% | 99.64% |
| 176.005 | 88.72% | 99.59% |
| 177.009 | 88.86% | 99.65% |
| 178.012 | 88.74% | 99.69% |
| 179.016 | 88.78% | 99.58% |
| 180.019 | 89.13% | 99.64% |
| 181.002 | 88.84% | 99.62% |
| 182.026 | 89.05% | 99.63% |
| 183.009 | 89.15% | 99.67% |
| 184.013 | 89.29% | 99.69% |
| 185.016 | 89.16% | 99.67% |
| 186.020 | 89.17% | 99.62% |
| 187.003 | 89.16% | 99.59% |
| 188.006 | 88.86% | 99.61% |
| 189.010 | 88.53% | 99.63% |
| 190.013 | 88.88% | 99.62% |
| 191.017 | 88.92% | 99.64% |
| 192.000 | 88.77% | 99.60% |
| 193.004 | 88.46% | 99.63% |
| 194.007 | 88.91% | 99.66% |
| 195.011 | 89.22% | 99.67% |
| 196.014 | 89.32% | 99.68% |
| 197.018 | 89.20% | 99.67% |
| 198.001 | 88.18% | 99.63% |
| 199.004 | 89.04% | 99.64% |
| 200.008 | 88.52% | 99.55% |
| 201.011 | 88.31% | 99.55% |
| 202.015 | 88.22% | 99.59% |
| 203.018 | 89.00% | 99.61% |
| 204.001 | 88.23% | 99.62% |
| 205.005 | 88.12% | 99.52% |
| 206.008 | 87.38% | 99.58% |
| 207.012 | 88.38% | 99.57% |
| 208.015 | 88.16% | 99.61% |
| 209.019 | 88.54% | 99.55% |
| 210.002 | 88.76% | 99.57% |
| 211.005 | 88.64% | 99.55% |
| 212.009 | 88.17% | 99.62% |
| 213.012 | 88.66% | 99.55% |
| 214.016 | 88.42% | 99.59% |
| 215.020 | 88.33% | 99.57% |
| 216.003 | 87.92% | 99.52% |
| 217.006 | 88.17% | 99.57% |
| 218.010 | 88.80% | 99.67% |
| 219.013 | 88.58% | 99.59% |
| 220.017 | 89.10% | 99.67% |
| 221.020 | 89.12% | 99.65% |
| 222.003 | 88.41% | 99.60% |
| 223.007 | 88.56% | 99.57% |
| 224.010 | 88.14% | 99.57% |
| 225.034 | 88.64% | 99.57% |
| 226.017 | 89.10% | 99.58% |
| 227.000 | 89.43% | 99.61% |
| 228.004 | 89.02% | 99.58% |
| 229.028 | 89.01% | 99.56% |
| 230.011 | 89.19% | 99.58% |
| 231.014 | 88.86% | 99.63% |
| 232.018 | 88.57% | 99.63% |
| 233.001 | 89.29% | 99.60% |
| 234.004 | 89.29% | 99.63% |
| 235.008 | 88.74% | 99.60% |
| 236.012 | 89.04% | 99.64% |
| 237.015 | 88.69% | 99.57% |
| 238.019 | 87.85% | 99.55% |
| 239.002 | 88.80% | 99.49% |
| 240.005 | 88.89% | 99.60% |
| 241.009 | 88.88% | 99.62% |
| 242.012 | 89.08% | 99.59% |
| 243.016 | 89.16% | 99.58% |
| 244.019 | 89.32% | 99.58% |
| 245.002 | 89.41% | 99.59% |
| 246.006 | 89.32% | 99.58% |
| 247.009 | 89.41% | 99.58% |
| 248.013 | 89.80% | 99.59% |
| 249.016 | 89.99% | 99.58% |
| 250.020 | 89.87% | 99.62% |
| 251.003 | 89.86% | 99.61% |
| 252.006 | 89.98% | 99.66% |
| 253.010 | 89.98% | 99.63% |
| 254.013 | 90.20% | 99.61% |
| 255.017 | 90.19% | 99.66% |
| 256.000 | 90.17% | 99.64% |
| 257.004 | 90.02% | 99.62% |
| 258.007 | 90.21% | 99.65% |
| 259.011 | 90.12% | 99.64% |
| 260.014 | 90.24% | 99.63% |
| 261.018 | 90.34% | 99.64% |
| 262.001 | 90.35% | 99.65% |
| 263.004 | 90.47% | 99.64% |
| 264.008 | 90.55% | 99.66% |
| 265.011 | 90.53% | 99.66% |
| 266.015 | 90.69% | 99.66% |
| 267.018 | 90.68% | 99.69% |
| 268.001 | 90.77% | 99.68% |
| 269.005 | 90.73% | 99.67% |
| 270.008 | 90.59% | 99.68% |
| 271.012 | 90.65% | 99.66% |
| 272.015 | 90.80% | 99.67% |
| 273.019 | 90.78% | 99.68% |
| 274.002 | 90.70% | 99.69% |
| 275.005 | 90.75% | 99.67% |
| 276.009 | 90.73% | 99.70% |
| 277.012 | 90.76% | 99.68% |
| 278.016 | 90.62% | 99.70% |
| 279.040 | 90.81% | 99.71% |
| 280.003 | 90.80% | 99.70% |
| 281.006 | 90.90% | 99.70% |
| 282.010 | 90.98% | 99.72% |
| 283.013 | 90.83% | 99.67% |
| 284.017 | 91.01% | 99.71% |
| 285.020 | 90.78% | 99.70% |
| 286.003 | 90.77% | 99.72% |
| 287.007 | 90.93% | 99.67% |
| 288.010 | 90.95% | 99.70% |
| 289.014 | 91.02% | 99.69% |
| 290.017 | 90.86% | 99.72% |
| 291.000 | 90.89% | 99.73% |
| 292.004 | 90.92% | 99.72% |
| 293.007 | 90.93% | 99.70% |
| 294.011 | 90.93% | 99.70% |
| 295.014 | 90.99% | 99.70% |
| 296.018 | 91.09% | 99.72% |
| 297.001 | 91.05% | 99.73% |
| 298.004 | 91.08% | 99.70% |
| 299.008 | 91.15% | 99.73% |
| 300.012 | 91.03% | 99.73% |
| 301.015 | 91.09% | 99.71% |
| 302.019 | 91.06% | 99.72% |
| 303.002 | 91.01% | 99.73% |
| 304.005 | 91.02% | 99.74% |
| 305.009 | 91.20% | 99.71% |
| 306.012 | 91.10% | 99.72% |
| 307.016 | 91.10% | 99.71% |
| 308.019 | 91.09% | 99.70% |
| 309.002 | 91.10% | 99.73% |
| 310.006 | 91.07% | 99.73% |
| 311.009 | 91.11% | 99.72% |
| 312.013 | 91.10% | 99.71% |
| 313.016 | 91.15% | 99.69% |
| 314.020 | 91.13% | 99.70% |
| 315.003 | 91.17% | 99.70% |
| 316.006 | 91.16% | 99.71% |
| 317.010 | 91.13% | 99.70% |
| 318.013 | 91.21% | 99.69% |
| 319.017 | 91.24% | 99.69% |
| 320.000 | 91.28% | 99.69% |
| 321.004 | 91.21% | 99.72% |
| 322.007 | 91.24% | 99.71% |
| 323.011 | 91.33% | 99.70% |
| 324.014 | 91.29% | 99.68% |
| 325.018 | 91.26% | 99.70% |
| 326.001 | 91.22% | 99.71% |
| 327.004 | 91.19% | 99.66% |
| 328.008 | 91.32% | 99.71% |
| 329.011 | 91.18% | 99.72% |
| 330.015 | 91.13% | 99.72% |
| 331.018 | 91.14% | 99.73% |
| 332.001 | 91.23% | 99.70% |
| 333.005 | 91.25% | 99.72% |
| 334.008 | 91.19% | 99.70% |
| 335.012 | 91.19% | 99.70% |
| 336.036 | 91.23% | 99.72% |
| 337.019 | 91.23% | 99.71% |
| 338.002 | 91.18% | 99.71% |
| 339.005 | 91.23% | 99.72% |
| 340.009 | 91.20% | 99.73% |
| 341.012 | 91.27% | 99.73% |
| 342.016 | 91.34% | 99.71% |
| 343.020 | 91.26% | 99.73% |
| 344.003 | 91.25% | 99.74% |
| 345.006 | 91.26% | 99.72% |
| 346.010 | 91.31% | 99.72% |
| 347.013 | 91.17% | 99.74% |
| 348.017 | 91.26% | 99.71% |
| 349.020 | 91.19% | 99.70% |
| 350.003 | 91.32% | 99.73% |
| 351.007 | 91.30% | 99.70% |
| 352.010 | 91.18% | 99.71% |
| 353.014 | 91.15% | 99.68% |
| 354.017 | 91.12% | 99.67% |
| 355.000 | 91.08% | 99.69% |
| 356.004 | 91.14% | 99.69% |
| 357.007 | 91.20% | 99.69% |
| 358.011 | 91.20% | 99.69% |
| 359.014 | 91.30% | 99.71% |
| 360.018 | 91.17% | 99.66% |
| 361.001 | 91.23% | 99.66% |
| 362.004 | 91.21% | 99.65% |
| 363.008 | 91.20% | 99.67% |
| 364.012 | 91.22% | 99.68% |
| 365.015 | 91.24% | 99.67% |
| 366.019 | 91.25% | 99.68% |
| 367.002 | 91.32% | 99.67% |
| 368.005 | 91.28% | 99.67% |
| 369.009 | 91.24% | 99.67% |
| 370.012 | 91.30% | 99.68% |
| 371.016 | 91.28% | 99.68% |
| 372.019 | 91.29% | 99.70% |
| 373.002 | 91.32% | 99.70% |
| 374.006 | 91.30% | 99.69% |
| 375.009 | 91.24% | 99.71% |
| 376.013 | 91.21% | 99.71% |
| 377.016 | 91.21% | 99.70% |
| 378.020 | 91.21% | 99.70% |
| 379.003 | 91.22% | 99.69% |
| 380.006 | 91.28% | 99.70% |
| 381.010 | 91.28% | 99.69% |
| 382.034 | 91.25% | 99.69% |
| 383.017 | 91.24% | 99.69% |
| 384.000 | 91.29% | 99.69% |
| 385.004 | 91.29% | 99.69% |
| 386.007 | 91.30% | 99.69% |
| 387.011 | 91.34% | 99.68% |
| 388.014 | 91.26% | 99.68% |
| 389.018 | 91.24% | 99.68% |
| 390.001 | 91.24% | 99.68% |
| 391.004 | 91.22% | 99.68% |
| 392.008 | 91.24% | 99.68% |
| 393.011 | 91.26% | 99.68% |
| 394.015 | 91.30% | 99.68% |
| 395.018 | 91.29% | 99.69% |
| 396.001 | 91.26% | 99.70% |
| 397.005 | 91.28% | 99.70% |
| 398.008 | 91.33% | 99.70% |
| 399.012 | 91.31% | 99.70% |
| 400.015 | 91.35% | 99.70% |
| 401.019 | 91.33% | 99.69% |
| 402.002 | 91.31% | 99.71% |
| 403.005 | 91.33% | 99.70% |
| 404.009 | 91.37% | 99.69% |
| 405.012 | 91.33% | 99.69% |
| 406.016 | 91.32% | 99.69% |
| 407.020 | 91.31% | 99.69% |
| 408.003 | 91.31% | 99.70% |
| 409.027 | 91.34% | 99.70% |
| 410.010 | 91.30% | 99.69% |
| 411.013 | 91.31% | 99.70% |
| 412.017 | 91.30% | 99.70% |
| 413.020 | 91.31% | 99.69% |
| 414.003 | 91.31% | 99.69% |
| 415.007 | 91.29% | 99.68% |
| 416.010 | 91.28% | 99.68% |
| 417.014 | 91.25% | 99.68% |
| 418.017 | 91.27% | 99.69% |
| 419.000 | 91.27% | 99.68% |
| 420.004 | 91.29% | 99.68% |
| 421.007 | 91.31% | 99.67% |
| 422.011 | 91.31% | 99.67% |
| 423.014 | 91.31% | 99.66% |
| 424.018 | 91.29% | 99.67% |
| 425.001 | 91.34% | 99.67% |
| 426.004 | 91.36% | 99.67% |
| 427.008 | 91.36% | 99.66% |
| 428.012 | 91.36% | 99.66% |
| 429.015 | 91.35% | 99.65% |
| 430.019 | 91.38% | 99.65% |
| 431.002 | 91.41% | 99.66% |
| 432.005 | 91.36% | 99.66% |
| 433.009 | 91.32% | 99.67% |
| 434.012 | 91.39% | 99.66% |
| 435.016 | 91.43% | 99.67% |
| 436.019 | 91.40% | 99.68% |
| 437.002 | 91.35% | 99.68% |
| 438.006 | 91.38% | 99.67% |
| 439.009 | 91.34% | 99.66% |
| 440.013 | 91.33% | 99.65% |
| 441.016 | 91.37% | 99.66% |
| 442.020 | 91.35% | 99.66% |
| 443.003 | 91.35% | 99.66% |
| 444.006 | 91.38% | 99.66% |
| 445.010 | 91.41% | 99.66% |
| 446.013 | 91.42% | 99.66% |
| 447.037 | 91.45% | 99.66% |
| 448.000 | 91.46% | 99.66% |
| 449.004 | 91.39% | 99.66% |
| 450.007 | 91.40% | 99.66% |
| 451.011 | 91.39% | 99.66% |
| 452.014 | 91.41% | 99.66% |
| 453.018 | 91.36% | 99.66% |
| 454.001 | 91.40% | 99.66% |
| 455.004 | 91.39% | 99.67% |
| 456.008 | 91.38% | 99.67% |
| 457.011 | 91.42% | 99.66% |
| 458.015 | 91.41% | 99.68% |
| 459.018 | 91.37% | 99.69% |
| 460.001 | 91.44% | 99.69% |
| 461.005 | 91.40% | 99.67% |
| 462.008 | 91.36% | 99.68% |
| 463.012 | 91.36% | 99.66% |
| 464.015 | 91.43% | 99.66% |
| 465.019 | 91.36% | 99.65% |
| 466.002 | 91.40% | 99.65% |
| 467.005 | 91.37% | 99.65% |
| 468.029 | 91.32% | 99.66% |
| 469.012 | 91.32% | 99.66% |
| 470.016 | 91.31% | 99.67% |
| 471.020 | 91.33% | 99.67% |
| 472.003 | 91.33% | 99.68% |
| 473.006 | 91.37% | 99.69% |
| 474.010 | 91.34% | 99.69% |
| 475.013 | 91.36% | 99.68% |
| 476.017 | 91.40% | 99.68% |
| 477.020 | 91.41% | 99.70% |
| 478.024 | 91.41% | 99.68% |
| 479.007 | 91.39% | 99.68% |
| 480.010 | 91.42% | 99.69% |
| 481.014 | 91.40% | 99.68% |
| 482.017 | 91.40% | 99.68% |
| 483.000 | 91.40% | 99.68% |
| 484.004 | 91.40% | 99.68% |
| 485.007 | 91.39% | 99.68% |
| 486.011 | 91.39% | 99.68% |
| 487.014 | 91.38% | 99.68% |
| 488.018 | 91.38% | 99.68% |
| 489.001 | 91.37% | 99.67% |
| 490.004 | 91.37% | 99.68% |
| 491.008 | 91.38% | 99.69% |
| 492.012 | 91.38% | 99.69% |
| 493.015 | 91.37% | 99.69% |
| 494.019 | 91.38% | 99.68% |
| 495.002 | 91.37% | 99.68% |
| 496.005 | 91.38% | 99.68% |
| 497.009 | 91.38% | 99.67% |
| 498.012 | 91.38% | 99.66% |
| 499.016 | 91.38% | 99.66% |
| 500.019 | 91.41% | 99.67% |
| 501.002 | 91.40% | 99.67% |
| 502.006 | 91.39% | 99.66% |
| 503.009 | 91.39% | 99.66% |
| 504.013 | 91.39% | 99.67% |
+---------+--------+--------+