Training in progress epoch 0
Browse files- README.md +7 -293
- tf_model.h5 +1 -1
README.md
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss:
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- Train Accuracy: 0.
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- Validation Loss:
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- Validation Accuracy: 0.
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- Epoch:
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps':
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- training_precision: float32
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### Training results
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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| 47 |
-
| 10.
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| 48 |
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| 10.2496 | 0.0000 | 10.2481 | 0.0 | 1 |
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| 49 |
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| 10.2431 | 0.0000 | 10.2392 | 0.0 | 2 |
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| 50 |
-
| 10.2335 | 0.0000 | 10.2228 | 0.0 | 3 |
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| 51 |
-
| 10.2206 | 0.0000 | 10.2052 | 0.0 | 4 |
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| 52 |
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| 10.1995 | 0.0000 | 10.1853 | 0.0 | 5 |
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| 53 |
-
| 10.1808 | 0.0 | 10.1590 | 0.0 | 6 |
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| 54 |
-
| 10.1545 | 0.0000 | 10.1320 | 0.0 | 7 |
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| 55 |
-
| 10.1309 | 0.0000 | 10.0995 | 0.0000 | 8 |
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| 56 |
-
| 10.0928 | 0.0000 | 10.0661 | 0.0000 | 9 |
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| 57 |
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| 10.0560 | 0.0001 | 10.0235 | 0.0001 | 10 |
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| 58 |
-
| 10.0210 | 0.0002 | 9.9788 | 0.0004 | 11 |
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| 59 |
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| 9.9771 | 0.0009 | 9.9368 | 0.0025 | 12 |
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| 60 |
-
| 9.9346 | 0.0031 | 9.8751 | 0.0085 | 13 |
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| 61 |
-
| 9.8850 | 0.0076 | 9.8226 | 0.0164 | 14 |
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| 62 |
-
| 9.8383 | 0.0139 | 9.7728 | 0.0207 | 15 |
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| 63 |
-
| 9.7859 | 0.0191 | 9.7087 | 0.0218 | 16 |
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| 64 |
-
| 9.7297 | 0.0219 | 9.6522 | 0.0219 | 17 |
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| 65 |
-
| 9.6682 | 0.0232 | 9.5955 | 0.0219 | 18 |
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| 66 |
-
| 9.6069 | 0.0230 | 9.5270 | 0.0222 | 19 |
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| 67 |
-
| 9.5499 | 0.0231 | 9.4594 | 0.0224 | 20 |
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| 68 |
-
| 9.4948 | 0.0228 | 9.4100 | 0.0220 | 21 |
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| 69 |
-
| 9.4330 | 0.0228 | 9.3543 | 0.0220 | 22 |
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| 70 |
-
| 9.3670 | 0.0229 | 9.2878 | 0.0219 | 23 |
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| 71 |
-
| 9.3224 | 0.0226 | 9.2113 | 0.0225 | 24 |
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| 72 |
-
| 9.2579 | 0.0230 | 9.1693 | 0.0221 | 25 |
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| 73 |
-
| 9.1997 | 0.0230 | 9.1246 | 0.0219 | 26 |
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| 74 |
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| 9.1412 | 0.0230 | 9.0661 | 0.0222 | 27 |
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| 75 |
-
| 9.0875 | 0.0232 | 9.0187 | 0.0223 | 28 |
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| 76 |
-
| 9.0569 | 0.0227 | 8.9709 | 0.0222 | 29 |
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| 77 |
-
| 9.0051 | 0.0230 | 8.9358 | 0.0222 | 30 |
|
| 78 |
-
| 8.9626 | 0.0231 | 8.8961 | 0.0224 | 31 |
|
| 79 |
-
| 8.9083 | 0.0233 | 8.9044 | 0.0215 | 32 |
|
| 80 |
-
| 8.8926 | 0.0230 | 8.8529 | 0.0219 | 33 |
|
| 81 |
-
| 8.8608 | 0.0229 | 8.8042 | 0.0225 | 34 |
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| 82 |
-
| 8.8363 | 0.0229 | 8.7768 | 0.0223 | 35 |
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| 83 |
-
| 8.7860 | 0.0231 | 8.7670 | 0.0218 | 36 |
|
| 84 |
-
| 8.7825 | 0.0227 | 8.7143 | 0.0225 | 37 |
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| 85 |
-
| 8.7257 | 0.0235 | 8.7171 | 0.0220 | 38 |
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| 86 |
-
| 8.7300 | 0.0228 | 8.6806 | 0.0222 | 39 |
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| 87 |
-
| 8.7047 | 0.0227 | 8.6295 | 0.0228 | 40 |
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| 88 |
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| 8.6880 | 0.0228 | 8.6459 | 0.0224 | 41 |
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| 89 |
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| 8.6516 | 0.0232 | 8.6152 | 0.0224 | 42 |
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| 90 |
-
| 8.6330 | 0.0230 | 8.6115 | 0.0220 | 43 |
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| 91 |
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| 8.6034 | 0.0231 | 8.5696 | 0.0223 | 44 |
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| 92 |
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| 8.6160 | 0.0225 | 8.5656 | 0.0223 | 45 |
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| 93 |
-
| 8.5749 | 0.0230 | 8.5517 | 0.0222 | 46 |
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| 94 |
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| 8.5638 | 0.0229 | 8.5393 | 0.0219 | 47 |
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| 95 |
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| 8.5395 | 0.0229 | 8.5066 | 0.0220 | 48 |
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| 96 |
-
| 8.5059 | 0.0232 | 8.4754 | 0.0224 | 49 |
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| 97 |
-
| 8.5014 | 0.0231 | 8.4696 | 0.0221 | 50 |
|
| 98 |
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| 8.4760 | 0.0233 | 8.4578 | 0.0221 | 51 |
|
| 99 |
-
| 8.4525 | 0.0231 | 8.4279 | 0.0221 | 52 |
|
| 100 |
-
| 8.4416 | 0.0232 | 8.4234 | 0.0220 | 53 |
|
| 101 |
-
| 8.4381 | 0.0229 | 8.4291 | 0.0219 | 54 |
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| 102 |
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| 8.4099 | 0.0232 | 8.3940 | 0.0220 | 55 |
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| 103 |
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| 8.3914 | 0.0234 | 8.3733 | 0.0222 | 56 |
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| 104 |
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| 8.3824 | 0.0231 | 8.3500 | 0.0225 | 57 |
|
| 105 |
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| 8.3825 | 0.0228 | 8.3478 | 0.0220 | 58 |
|
| 106 |
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| 8.3479 | 0.0233 | 8.3204 | 0.0223 | 59 |
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| 107 |
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| 8.3371 | 0.0232 | 8.3120 | 0.0221 | 60 |
|
| 108 |
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| 8.3434 | 0.0228 | 8.3098 | 0.0219 | 61 |
|
| 109 |
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| 8.3141 | 0.0232 | 8.2805 | 0.0224 | 62 |
|
| 110 |
-
| 8.2891 | 0.0232 | 8.2660 | 0.0223 | 63 |
|
| 111 |
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| 8.2822 | 0.0232 | 8.2824 | 0.0220 | 64 |
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| 112 |
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| 8.2628 | 0.0233 | 8.2788 | 0.0216 | 65 |
|
| 113 |
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| 8.2724 | 0.0229 | 8.2309 | 0.0224 | 66 |
|
| 114 |
-
| 8.2621 | 0.0229 | 8.2434 | 0.0218 | 67 |
|
| 115 |
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| 8.2283 | 0.0235 | 8.2072 | 0.0223 | 68 |
|
| 116 |
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| 8.2398 | 0.0227 | 8.2305 | 0.0217 | 69 |
|
| 117 |
-
| 8.2253 | 0.0226 | 8.1947 | 0.0222 | 70 |
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| 118 |
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| 8.2031 | 0.0230 | 8.1786 | 0.0219 | 71 |
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| 119 |
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| 8.2017 | 0.0229 | 8.1876 | 0.0219 | 72 |
|
| 120 |
-
| 8.1812 | 0.0231 | 8.1746 | 0.0218 | 73 |
|
| 121 |
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| 8.1871 | 0.0230 | 8.1384 | 0.0220 | 74 |
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| 122 |
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| 8.1542 | 0.0231 | 8.1167 | 0.0225 | 75 |
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| 123 |
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| 8.1541 | 0.0230 | 8.1213 | 0.0222 | 76 |
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| 124 |
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| 8.1595 | 0.0227 | 8.1243 | 0.0218 | 77 |
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| 125 |
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| 8.1508 | 0.0229 | 8.0881 | 0.0222 | 78 |
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| 126 |
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| 8.1222 | 0.0229 | 8.0818 | 0.0223 | 79 |
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| 127 |
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| 8.1262 | 0.0226 | 8.0768 | 0.0222 | 80 |
|
| 128 |
-
| 8.0922 | 0.0231 | 8.0586 | 0.0224 | 81 |
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| 129 |
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| 8.0733 | 0.0233 | 8.0438 | 0.0222 | 82 |
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| 130 |
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| 8.0667 | 0.0230 | 8.0528 | 0.0219 | 83 |
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| 131 |
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| 8.0645 | 0.0228 | 8.0459 | 0.0218 | 84 |
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| 132 |
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| 8.0571 | 0.0228 | 8.0107 | 0.0223 | 85 |
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| 133 |
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| 8.0443 | 0.0228 | 8.0088 | 0.0219 | 86 |
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| 134 |
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| 8.0193 | 0.0232 | 8.0000 | 0.0222 | 87 |
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| 135 |
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| 8.0176 | 0.0229 | 7.9695 | 0.0223 | 88 |
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| 136 |
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| 8.0021 | 0.0231 | 7.9909 | 0.0217 | 89 |
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| 137 |
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| 7.9930 | 0.0231 | 7.9529 | 0.0224 | 90 |
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| 138 |
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| 7.9868 | 0.0228 | 7.9500 | 0.0219 | 91 |
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| 139 |
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| 7.9579 | 0.0232 | 7.9222 | 0.0224 | 92 |
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| 140 |
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| 7.9576 | 0.0231 | 7.9682 | 0.0214 | 93 |
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| 141 |
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| 7.9475 | 0.0231 | 7.9137 | 0.0222 | 94 |
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| 142 |
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| 7.9334 | 0.0233 | 7.8913 | 0.0222 | 95 |
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| 143 |
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| 7.9238 | 0.0231 | 7.9050 | 0.0223 | 96 |
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| 144 |
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| 7.9155 | 0.0229 | 7.8928 | 0.0218 | 97 |
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| 145 |
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| 7.8980 | 0.0230 | 7.9026 | 0.0218 | 98 |
|
| 146 |
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| 7.8889 | 0.0231 | 7.8516 | 0.0221 | 99 |
|
| 147 |
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| 7.8879 | 0.0231 | 7.8706 | 0.0218 | 100 |
|
| 148 |
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| 7.8818 | 0.0228 | 7.8477 | 0.0219 | 101 |
|
| 149 |
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| 7.8535 | 0.0232 | 7.8226 | 0.0222 | 102 |
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| 150 |
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| 7.8544 | 0.0229 | 7.8108 | 0.0223 | 103 |
|
| 151 |
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| 7.8325 | 0.0232 | 7.7939 | 0.0219 | 104 |
|
| 152 |
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| 7.8297 | 0.0231 | 7.8053 | 0.0220 | 105 |
|
| 153 |
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| 7.7939 | 0.0236 | 7.7855 | 0.0224 | 106 |
|
| 154 |
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| 7.7914 | 0.0235 | 7.7769 | 0.0223 | 107 |
|
| 155 |
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| 7.7782 | 0.0237 | 7.7665 | 0.0225 | 108 |
|
| 156 |
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| 7.7817 | 0.0237 | 7.7387 | 0.0229 | 109 |
|
| 157 |
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| 7.7861 | 0.0235 | 7.7325 | 0.0233 | 110 |
|
| 158 |
-
| 7.7473 | 0.0242 | 7.7006 | 0.0235 | 111 |
|
| 159 |
-
| 7.7386 | 0.0240 | 7.7212 | 0.0232 | 112 |
|
| 160 |
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| 7.7177 | 0.0245 | 7.6964 | 0.0236 | 113 |
|
| 161 |
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| 7.7402 | 0.0240 | 7.6889 | 0.0237 | 114 |
|
| 162 |
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| 7.7172 | 0.0242 | 7.6520 | 0.0240 | 115 |
|
| 163 |
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| 7.6940 | 0.0247 | 7.6640 | 0.0240 | 116 |
|
| 164 |
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| 7.6710 | 0.0249 | 7.6605 | 0.0238 | 117 |
|
| 165 |
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| 7.6630 | 0.0251 | 7.6351 | 0.0244 | 118 |
|
| 166 |
-
| 7.6354 | 0.0252 | 7.6229 | 0.0243 | 119 |
|
| 167 |
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| 7.6368 | 0.0254 | 7.6207 | 0.0245 | 120 |
|
| 168 |
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| 7.6311 | 0.0254 | 7.6041 | 0.0242 | 121 |
|
| 169 |
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| 7.6209 | 0.0254 | 7.5976 | 0.0245 | 122 |
|
| 170 |
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| 7.6226 | 0.0254 | 7.5619 | 0.0253 | 123 |
|
| 171 |
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| 7.5991 | 0.0256 | 7.5650 | 0.0242 | 124 |
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| 172 |
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| 7.5802 | 0.0255 | 7.5633 | 0.0245 | 125 |
|
| 173 |
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| 7.5744 | 0.0255 | 7.5309 | 0.0251 | 126 |
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| 174 |
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| 7.5704 | 0.0256 | 7.5485 | 0.0244 | 127 |
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| 175 |
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| 7.5639 | 0.0255 | 7.5277 | 0.0245 | 128 |
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| 176 |
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| 7.5092 | 0.0260 | 7.4999 | 0.0249 | 129 |
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| 177 |
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| 7.5211 | 0.0256 | 7.4692 | 0.0253 | 130 |
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| 178 |
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| 7.4986 | 0.0260 | 7.4531 | 0.0257 | 131 |
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| 179 |
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| 7.4903 | 0.0258 | 7.4624 | 0.0251 | 132 |
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| 180 |
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| 7.4924 | 0.0258 | 7.4620 | 0.0252 | 133 |
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| 181 |
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| 7.4669 | 0.0261 | 7.4557 | 0.0251 | 134 |
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| 182 |
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| 7.4734 | 0.0258 | 7.4125 | 0.0258 | 135 |
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| 183 |
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| 7.4397 | 0.0263 | 7.4058 | 0.0257 | 136 |
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| 184 |
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| 7.4291 | 0.0265 | 7.4043 | 0.0260 | 137 |
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| 185 |
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| 7.4160 | 0.0267 | 7.4004 | 0.0257 | 138 |
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| 186 |
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| 7.3910 | 0.0268 | 7.3609 | 0.0262 | 139 |
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| 187 |
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| 7.3908 | 0.0268 | 7.3413 | 0.0261 | 140 |
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| 188 |
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| 7.3792 | 0.0268 | 7.3105 | 0.0268 | 141 |
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| 189 |
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| 7.3743 | 0.0272 | 7.3053 | 0.0269 | 142 |
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| 190 |
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| 7.3295 | 0.0273 | 7.3098 | 0.0267 | 143 |
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| 191 |
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| 7.3447 | 0.0274 | 7.2675 | 0.0274 | 144 |
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| 192 |
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| 7.3185 | 0.0280 | 7.2751 | 0.0275 | 145 |
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| 193 |
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| 7.3191 | 0.0271 | 7.2432 | 0.0280 | 146 |
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| 194 |
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| 7.2709 | 0.0281 | 7.2580 | 0.0272 | 147 |
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| 195 |
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| 7.2910 | 0.0278 | 7.2600 | 0.0271 | 148 |
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| 196 |
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| 7.2615 | 0.0281 | 7.2605 | 0.0266 | 149 |
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| 197 |
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| 7.2485 | 0.0283 | 7.1975 | 0.0279 | 150 |
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| 198 |
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| 7.2472 | 0.0279 | 7.1838 | 0.0279 | 151 |
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| 199 |
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| 7.2237 | 0.0283 | 7.2025 | 0.0271 | 152 |
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| 200 |
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| 7.1949 | 0.0285 | 7.1577 | 0.0281 | 153 |
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| 201 |
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| 7.1935 | 0.0284 | 7.1602 | 0.0279 | 154 |
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| 202 |
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| 7.1955 | 0.0283 | 7.1261 | 0.0285 | 155 |
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| 203 |
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| 7.1604 | 0.0287 | 7.0959 | 0.0283 | 156 |
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| 204 |
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| 7.1419 | 0.0288 | 7.0961 | 0.0287 | 157 |
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| 205 |
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| 7.1329 | 0.0290 | 7.0951 | 0.0281 | 158 |
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| 206 |
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| 7.1233 | 0.0289 | 7.0845 | 0.0284 | 159 |
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| 207 |
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| 7.1062 | 0.0291 | 7.0783 | 0.0281 | 160 |
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| 208 |
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| 7.0831 | 0.0290 | 7.0597 | 0.0283 | 161 |
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| 209 |
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| 7.0875 | 0.0290 | 7.0208 | 0.0285 | 162 |
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| 210 |
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| 7.0634 | 0.0289 | 7.0306 | 0.0286 | 163 |
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| 211 |
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| 7.0625 | 0.0288 | 7.0036 | 0.0288 | 164 |
|
| 212 |
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| 7.0344 | 0.0292 | 6.9986 | 0.0284 | 165 |
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| 213 |
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| 7.0387 | 0.0291 | 6.9902 | 0.0289 | 166 |
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| 214 |
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| 7.0368 | 0.0288 | 6.9715 | 0.0287 | 167 |
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| 215 |
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| 7.0066 | 0.0293 | 6.9598 | 0.0288 | 168 |
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| 216 |
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| 6.9853 | 0.0293 | 6.9438 | 0.0288 | 169 |
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| 217 |
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| 6.9692 | 0.0295 | 6.9572 | 0.0284 | 170 |
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| 218 |
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| 6.9751 | 0.0293 | 6.9209 | 0.0291 | 171 |
|
| 219 |
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| 6.9404 | 0.0301 | 6.9052 | 0.0287 | 172 |
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| 220 |
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| 6.9248 | 0.0299 | 6.9202 | 0.0292 | 173 |
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| 221 |
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| 6.9254 | 0.0297 | 6.8947 | 0.0290 | 174 |
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| 222 |
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| 6.8793 | 0.0303 | 6.8551 | 0.0300 | 175 |
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| 223 |
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| 6.8970 | 0.0298 | 6.8497 | 0.0298 | 176 |
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| 224 |
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| 6.8770 | 0.0301 | 6.8523 | 0.0295 | 177 |
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| 225 |
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| 6.8807 | 0.0297 | 6.8162 | 0.0297 | 178 |
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| 226 |
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| 6.8757 | 0.0299 | 6.8129 | 0.0301 | 179 |
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| 227 |
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| 6.8559 | 0.0302 | 6.8075 | 0.0299 | 180 |
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| 228 |
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| 6.8302 | 0.0307 | 6.7924 | 0.0300 | 181 |
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| 229 |
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| 6.8131 | 0.0304 | 6.7848 | 0.0298 | 182 |
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| 230 |
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| 6.7881 | 0.0308 | 6.7749 | 0.0297 | 183 |
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| 231 |
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| 6.7841 | 0.0307 | 6.7333 | 0.0306 | 184 |
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| 232 |
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| 6.7786 | 0.0311 | 6.7726 | 0.0300 | 185 |
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| 233 |
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| 6.7525 | 0.0313 | 6.7216 | 0.0308 | 186 |
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| 234 |
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| 6.7551 | 0.0309 | 6.7376 | 0.0302 | 187 |
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| 6.7458 | 0.0309 | 6.6722 | 0.0307 | 188 |
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| 6.7409 | 0.0307 | 6.7092 | 0.0305 | 189 |
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| 6.7085 | 0.0313 | 6.6670 | 0.0312 | 190 |
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| 6.7025 | 0.0311 | 6.6755 | 0.0307 | 191 |
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| 239 |
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| 6.7070 | 0.0311 | 6.6865 | 0.0303 | 192 |
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| 240 |
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| 6.6706 | 0.0312 | 6.6554 | 0.0306 | 193 |
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| 241 |
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| 6.6932 | 0.0307 | 6.6252 | 0.0308 | 194 |
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| 242 |
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| 6.6605 | 0.0314 | 6.6228 | 0.0309 | 195 |
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| 243 |
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| 6.6615 | 0.0313 | 6.5984 | 0.0309 | 196 |
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| 6.6251 | 0.0317 | 6.5973 | 0.0305 | 197 |
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| 6.6413 | 0.0315 | 6.5968 | 0.0308 | 198 |
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| 6.6335 | 0.0313 | 6.5784 | 0.0315 | 199 |
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| 6.6021 | 0.0317 | 6.6148 | 0.0301 | 200 |
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| 248 |
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| 6.6055 | 0.0316 | 6.5620 | 0.0312 | 201 |
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| 6.5753 | 0.0322 | 6.5174 | 0.0314 | 202 |
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| 250 |
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| 6.5534 | 0.0319 | 6.5237 | 0.0316 | 203 |
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| 6.5335 | 0.0325 | 6.5254 | 0.0313 | 204 |
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| 252 |
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| 6.5224 | 0.0322 | 6.5104 | 0.0313 | 205 |
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| 253 |
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| 6.5216 | 0.0323 | 6.4941 | 0.0312 | 206 |
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| 254 |
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| 6.5267 | 0.0317 | 6.5140 | 0.0305 | 207 |
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| 255 |
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| 6.5037 | 0.0322 | 6.4885 | 0.0313 | 208 |
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| 256 |
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| 6.5072 | 0.0322 | 6.4380 | 0.0316 | 209 |
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| 257 |
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| 6.5171 | 0.0319 | 6.4570 | 0.0315 | 210 |
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| 258 |
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| 6.4631 | 0.0322 | 6.4434 | 0.0314 | 211 |
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| 259 |
-
| 6.4574 | 0.0323 | 6.4379 | 0.0316 | 212 |
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| 260 |
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| 6.4697 | 0.0321 | 6.4181 | 0.0314 | 213 |
|
| 261 |
-
| 6.4363 | 0.0325 | 6.3995 | 0.0320 | 214 |
|
| 262 |
-
| 6.4179 | 0.0324 | 6.3720 | 0.0322 | 215 |
|
| 263 |
-
| 6.4270 | 0.0322 | 6.3961 | 0.0317 | 216 |
|
| 264 |
-
| 6.4008 | 0.0327 | 6.3785 | 0.0320 | 217 |
|
| 265 |
-
| 6.4059 | 0.0325 | 6.3993 | 0.0314 | 218 |
|
| 266 |
-
| 6.3981 | 0.0325 | 6.3452 | 0.0323 | 219 |
|
| 267 |
-
| 6.4078 | 0.0320 | 6.3423 | 0.0321 | 220 |
|
| 268 |
-
| 6.3850 | 0.0325 | 6.3163 | 0.0324 | 221 |
|
| 269 |
-
| 6.3541 | 0.0328 | 6.3212 | 0.0324 | 222 |
|
| 270 |
-
| 6.3281 | 0.0331 | 6.3470 | 0.0314 | 223 |
|
| 271 |
-
| 6.3484 | 0.0328 | 6.3217 | 0.0319 | 224 |
|
| 272 |
-
| 6.3365 | 0.0328 | 6.2958 | 0.0325 | 225 |
|
| 273 |
-
| 6.3375 | 0.0322 | 6.3008 | 0.0320 | 226 |
|
| 274 |
-
| 6.3197 | 0.0326 | 6.2681 | 0.0324 | 227 |
|
| 275 |
-
| 6.3137 | 0.0327 | 6.2855 | 0.0317 | 228 |
|
| 276 |
-
| 6.2884 | 0.0329 | 6.2616 | 0.0317 | 229 |
|
| 277 |
-
| 6.2839 | 0.0329 | 6.2563 | 0.0321 | 230 |
|
| 278 |
-
| 6.2831 | 0.0326 | 6.2506 | 0.0319 | 231 |
|
| 279 |
-
| 6.2739 | 0.0326 | 6.2192 | 0.0327 | 232 |
|
| 280 |
-
| 6.2593 | 0.0329 | 6.2538 | 0.0320 | 233 |
|
| 281 |
-
| 6.2339 | 0.0332 | 6.2253 | 0.0317 | 234 |
|
| 282 |
-
| 6.2557 | 0.0329 | 6.2168 | 0.0324 | 235 |
|
| 283 |
-
| 6.2430 | 0.0329 | 6.2176 | 0.0321 | 236 |
|
| 284 |
-
| 6.2300 | 0.0328 | 6.1976 | 0.0327 | 237 |
|
| 285 |
-
| 6.2148 | 0.0331 | 6.2317 | 0.0316 | 238 |
|
| 286 |
-
| 6.2190 | 0.0332 | 6.1691 | 0.0326 | 239 |
|
| 287 |
-
| 6.2144 | 0.0329 | 6.1703 | 0.0318 | 240 |
|
| 288 |
-
| 6.1798 | 0.0333 | 6.1809 | 0.0319 | 241 |
|
| 289 |
-
| 6.1920 | 0.0330 | 6.1689 | 0.0326 | 242 |
|
| 290 |
-
| 6.1675 | 0.0333 | 6.1543 | 0.0328 | 243 |
|
| 291 |
-
| 6.1485 | 0.0338 | 6.1291 | 0.0328 | 244 |
|
| 292 |
-
| 6.1606 | 0.0330 | 6.1168 | 0.0328 | 245 |
|
| 293 |
-
| 6.1700 | 0.0330 | 6.1191 | 0.0325 | 246 |
|
| 294 |
-
| 6.1237 | 0.0341 | 6.1201 | 0.0326 | 247 |
|
| 295 |
-
| 6.1311 | 0.0333 | 6.1046 | 0.0327 | 248 |
|
| 296 |
-
| 6.1181 | 0.0335 | 6.0931 | 0.0325 | 249 |
|
| 297 |
-
| 6.1195 | 0.0331 | 6.1025 | 0.0327 | 250 |
|
| 298 |
-
| 6.1134 | 0.0332 | 6.0916 | 0.0324 | 251 |
|
| 299 |
-
| 6.0884 | 0.0337 | 6.0796 | 0.0328 | 252 |
|
| 300 |
-
| 6.0888 | 0.0336 | 6.0741 | 0.0327 | 253 |
|
| 301 |
-
| 6.0944 | 0.0332 | 6.0575 | 0.0326 | 254 |
|
| 302 |
-
| 6.0798 | 0.0337 | 6.0441 | 0.0328 | 255 |
|
| 303 |
-
| 6.0694 | 0.0336 | 6.0589 | 0.0327 | 256 |
|
| 304 |
-
| 6.0835 | 0.0333 | 6.0399 | 0.0333 | 257 |
|
| 305 |
-
| 6.0512 | 0.0337 | 6.0469 | 0.0329 | 258 |
|
| 306 |
-
| 6.0557 | 0.0337 | 6.0354 | 0.0327 | 259 |
|
| 307 |
-
| 6.0599 | 0.0332 | 6.0166 | 0.0330 | 260 |
|
| 308 |
-
| 6.0439 | 0.0336 | 6.0266 | 0.0331 | 261 |
|
| 309 |
-
| 6.0451 | 0.0338 | 6.0143 | 0.0331 | 262 |
|
| 310 |
-
| 6.0465 | 0.0333 | 5.9886 | 0.0334 | 263 |
|
| 311 |
-
| 6.0184 | 0.0341 | 6.0216 | 0.0329 | 264 |
|
| 312 |
-
| 6.0181 | 0.0340 | 6.0064 | 0.0330 | 265 |
|
| 313 |
-
| 5.9950 | 0.0338 | 6.0078 | 0.0321 | 266 |
|
| 314 |
-
| 5.9885 | 0.0339 | 5.9742 | 0.0331 | 267 |
|
| 315 |
-
| 5.9862 | 0.0337 | 5.9633 | 0.0335 | 268 |
|
| 316 |
-
| 5.9855 | 0.0341 | 5.9573 | 0.0331 | 269 |
|
| 317 |
-
| 5.9642 | 0.0342 | 5.9527 | 0.0331 | 270 |
|
| 318 |
-
| 5.9697 | 0.0342 | 5.9507 | 0.0334 | 271 |
|
| 319 |
-
| 5.9784 | 0.0341 | 5.9614 | 0.0328 | 272 |
|
| 320 |
-
| 5.9646 | 0.0342 | 5.9523 | 0.0326 | 273 |
|
| 321 |
-
| 5.9488 | 0.0342 | 5.9371 | 0.0330 | 274 |
|
| 322 |
-
| 5.9423 | 0.0345 | 5.9364 | 0.0329 | 275 |
|
| 323 |
-
| 5.9329 | 0.0344 | 5.9326 | 0.0334 | 276 |
|
| 324 |
-
| 5.9508 | 0.0335 | 5.9068 | 0.0338 | 277 |
|
| 325 |
-
| 5.9238 | 0.0345 | 5.9155 | 0.0337 | 278 |
|
| 326 |
-
| 5.9239 | 0.0339 | 5.9017 | 0.0336 | 279 |
|
| 327 |
-
| 5.9159 | 0.0339 | 5.8814 | 0.0336 | 280 |
|
| 328 |
-
| 5.8942 | 0.0344 | 5.8985 | 0.0336 | 281 |
|
| 329 |
-
| 5.9139 | 0.0346 | 5.8883 | 0.0341 | 282 |
|
| 330 |
-
| 5.8951 | 0.0343 | 5.9050 | 0.0331 | 283 |
|
| 331 |
-
| 5.8964 | 0.0341 | 5.8969 | 0.0335 | 284 |
|
| 332 |
-
| 5.9078 | 0.0342 | 5.8564 | 0.0343 | 285 |
|
| 333 |
-
| 5.8849 | 0.0343 | 5.8757 | 0.0337 | 286 |
|
| 334 |
|
| 335 |
|
| 336 |
### Framework versions
|
|
|
|
| 14 |
|
| 15 |
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
|
| 16 |
It achieves the following results on the evaluation set:
|
| 17 |
+
- Train Loss: 10.2868
|
| 18 |
+
- Train Accuracy: 0.0
|
| 19 |
+
- Validation Loss: 10.2891
|
| 20 |
+
- Validation Accuracy: 0.0
|
| 21 |
+
- Epoch: 0
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
|
|
| 37 |
### Training hyperparameters
|
| 38 |
|
| 39 |
The following hyperparameters were used during training:
|
| 40 |
+
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 223250, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 11750, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
|
| 41 |
- training_precision: float32
|
| 42 |
|
| 43 |
### Training results
|
| 44 |
|
| 45 |
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|
| 46 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
|
| 47 |
+
| 10.2868 | 0.0 | 10.2891 | 0.0 | 0 |
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| 48 |
|
| 49 |
|
| 50 |
### Framework versions
|
tf_model.h5
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 499741936
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:46ecc110ea17dee8e700cd2064a549e5fbf509cd884ec3c758fa09d5240704de
|
| 3 |
size 499741936
|