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makhataei
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qa-persian-mdeberta-v3-base-squad2

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deberta-v2
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End of training

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  1. README.md +81 -81
  2. model.safetensors +1 -1
  3. runs/Mar06_20-20-12_Software-AI/events.out.tfevents.1709743814.Software-AI.118212.35 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -34,7 +34,7 @@ More information needed
34
  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1.52587890625e-08
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  - train_batch_size: 14
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  - eval_batch_size: 14
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  - seed: 42
@@ -46,105 +46,105 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 4.8592 | 1.0 | 17 | 5.1273 |
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  | 4.9328 | 2.0 | 34 | 5.1273 |
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- | 4.9114 | 3.0 | 51 | 5.1273 |
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- | 4.8832 | 4.0 | 68 | 5.1273 |
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  | 4.9652 | 5.0 | 85 | 5.1273 |
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  | 4.8964 | 6.0 | 102 | 5.1273 |
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- | 4.8318 | 7.0 | 119 | 5.1273 |
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- | 4.8346 | 8.0 | 136 | 5.1273 |
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- | 4.8818 | 9.0 | 153 | 5.1273 |
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- | 4.8991 | 10.0 | 170 | 5.1273 |
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- | 4.9173 | 11.0 | 187 | 5.1273 |
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- | 4.9175 | 12.0 | 204 | 5.1273 |
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- | 4.8557 | 13.0 | 221 | 5.1273 |
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- | 4.885 | 14.0 | 238 | 5.1273 |
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- | 4.85 | 15.0 | 255 | 5.1273 |
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- | 4.8757 | 16.0 | 272 | 5.1273 |
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- | 4.8558 | 17.0 | 289 | 5.1273 |
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- | 4.8988 | 18.0 | 306 | 5.1273 |
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- | 4.8438 | 19.0 | 323 | 5.1273 |
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  | 4.8985 | 20.0 | 340 | 5.1273 |
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- | 4.8632 | 21.0 | 357 | 5.1273 |
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- | 4.9089 | 22.0 | 374 | 5.1273 |
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- | 4.8961 | 23.0 | 391 | 5.1273 |
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- | 4.8146 | 24.0 | 408 | 5.1273 |
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- | 4.9511 | 25.0 | 425 | 5.1273 |
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- | 4.916 | 26.0 | 442 | 5.1273 |
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  | 4.8573 | 27.0 | 459 | 5.1273 |
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- | 4.8314 | 28.0 | 476 | 5.1273 |
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  | 4.8523 | 29.0 | 493 | 5.1273 |
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- | 4.8641 | 30.0 | 510 | 5.1273 |
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- | 4.9481 | 31.0 | 527 | 5.1273 |
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- | 4.9747 | 32.0 | 544 | 5.1273 |
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- | 4.9189 | 33.0 | 561 | 5.1273 |
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- | 4.9649 | 34.0 | 578 | 5.1273 |
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- | 4.9063 | 35.0 | 595 | 5.1273 |
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- | 4.8964 | 36.0 | 612 | 5.1273 |
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- | 4.929 | 37.0 | 629 | 5.1273 |
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- | 4.9711 | 38.0 | 646 | 5.1273 |
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- | 4.9267 | 39.0 | 663 | 5.1273 |
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- | 4.9513 | 40.0 | 680 | 5.1273 |
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- | 4.9562 | 41.0 | 697 | 5.1273 |
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- | 4.8921 | 42.0 | 714 | 5.1273 |
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- | 4.9999 | 43.0 | 731 | 5.1273 |
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- | 5.0168 | 44.0 | 748 | 5.1273 |
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- | 4.9921 | 45.0 | 765 | 5.1273 |
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- | 4.9444 | 46.0 | 782 | 5.1273 |
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- | 4.9714 | 47.0 | 799 | 5.1273 |
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  | 4.9723 | 48.0 | 816 | 5.1273 |
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  | 4.9641 | 49.0 | 833 | 5.1273 |
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- | 4.9619 | 50.0 | 850 | 5.1273 |
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- | 4.966 | 51.0 | 867 | 5.1273 |
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- | 4.9755 | 52.0 | 884 | 5.1273 |
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- | 5.0266 | 53.0 | 901 | 5.1273 |
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- | 5.0179 | 54.0 | 918 | 5.1273 |
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- | 4.9841 | 55.0 | 935 | 5.1273 |
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  | 4.9846 | 56.0 | 952 | 5.1273 |
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- | 5.0145 | 57.0 | 969 | 5.1273 |
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- | 5.0592 | 58.0 | 986 | 5.1273 |
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  | 4.9787 | 59.0 | 1003 | 5.1273 |
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- | 5.0564 | 60.0 | 1020 | 5.1273 |
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- | 5.0235 | 61.0 | 1037 | 5.1273 |
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- | 4.9636 | 62.0 | 1054 | 5.1273 |
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- | 5.0478 | 63.0 | 1071 | 5.1273 |
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- | 4.9654 | 64.0 | 1088 | 5.1273 |
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- | 5.063 | 65.0 | 1105 | 5.1273 |
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- | 5.0672 | 66.0 | 1122 | 5.1273 |
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- | 5.0423 | 67.0 | 1139 | 5.1273 |
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- | 5.006 | 68.0 | 1156 | 5.1273 |
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- | 4.9886 | 69.0 | 1173 | 5.1273 |
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- | 5.0529 | 70.0 | 1190 | 5.1273 |
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- | 5.1072 | 71.0 | 1207 | 5.1273 |
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  | 5.016 | 72.0 | 1224 | 5.1273 |
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- | 5.0382 | 73.0 | 1241 | 5.1273 |
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  | 5.032 | 74.0 | 1258 | 5.1273 |
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- | 5.0458 | 75.0 | 1275 | 5.1273 |
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  | 5.0734 | 76.0 | 1292 | 5.1273 |
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- | 5.0058 | 77.0 | 1309 | 5.1273 |
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  | 5.027 | 78.0 | 1326 | 5.1273 |
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- | 5.0381 | 79.0 | 1343 | 5.1273 |
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- | 5.1037 | 80.0 | 1360 | 5.1273 |
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  | 5.0209 | 81.0 | 1377 | 5.1273 |
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- | 5.044 | 82.0 | 1394 | 5.1273 |
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- | 4.9924 | 83.0 | 1411 | 5.1273 |
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- | 5.0461 | 84.0 | 1428 | 5.1273 |
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- | 5.0414 | 85.0 | 1445 | 5.1273 |
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  | 5.0593 | 86.0 | 1462 | 5.1273 |
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- | 5.1126 | 87.0 | 1479 | 5.1273 |
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  | 5.0125 | 88.0 | 1496 | 5.1273 |
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- | 5.0924 | 89.0 | 1513 | 5.1273 |
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- | 5.068 | 90.0 | 1530 | 5.1273 |
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- | 5.0961 | 91.0 | 1547 | 5.1273 |
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- | 5.0842 | 92.0 | 1564 | 5.1273 |
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- | 5.0983 | 93.0 | 1581 | 5.1273 |
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  | 5.0251 | 94.0 | 1598 | 5.1273 |
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- | 5.0905 | 95.0 | 1615 | 5.1273 |
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- | 5.1353 | 96.0 | 1632 | 5.1273 |
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  | 5.1103 | 97.0 | 1649 | 5.1273 |
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- | 5.0243 | 98.0 | 1666 | 5.1273 |
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- | 5.0913 | 99.0 | 1683 | 5.1273 |
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  | 5.1083 | 100.0 | 1700 | 5.1273 |
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34
  ### Training hyperparameters
35
 
36
  The following hyperparameters were used during training:
37
+ - learning_rate: 1e-07
38
  - train_batch_size: 14
39
  - eval_batch_size: 14
40
  - seed: 42
 
46
 
47
  | Training Loss | Epoch | Step | Validation Loss |
48
  |:-------------:|:-----:|:----:|:---------------:|
49
+ | 4.8591 | 1.0 | 17 | 5.1273 |
50
  | 4.9328 | 2.0 | 34 | 5.1273 |
51
+ | 4.9113 | 3.0 | 51 | 5.1273 |
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+ | 4.8829 | 4.0 | 68 | 5.1273 |
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  | 4.9652 | 5.0 | 85 | 5.1273 |
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  | 4.8964 | 6.0 | 102 | 5.1273 |
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+ | 4.8316 | 7.0 | 119 | 5.1273 |
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+ | 4.8343 | 8.0 | 136 | 5.1273 |
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+ | 4.8819 | 9.0 | 153 | 5.1273 |
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+ | 4.8986 | 10.0 | 170 | 5.1273 |
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+ | 4.9171 | 11.0 | 187 | 5.1273 |
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+ | 4.9171 | 12.0 | 204 | 5.1273 |
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+ | 4.8551 | 13.0 | 221 | 5.1273 |
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+ | 4.8842 | 14.0 | 238 | 5.1273 |
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+ | 4.8491 | 15.0 | 255 | 5.1273 |
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+ | 4.8761 | 16.0 | 272 | 5.1273 |
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+ | 4.8561 | 17.0 | 289 | 5.1273 |
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+ | 4.8983 | 18.0 | 306 | 5.1273 |
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+ | 4.844 | 19.0 | 323 | 5.1273 |
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  | 4.8985 | 20.0 | 340 | 5.1273 |
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+ | 4.8629 | 21.0 | 357 | 5.1273 |
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+ | 4.9092 | 22.0 | 374 | 5.1273 |
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+ | 4.8956 | 23.0 | 391 | 5.1273 |
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+ | 4.8141 | 24.0 | 408 | 5.1273 |
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+ | 4.9507 | 25.0 | 425 | 5.1273 |
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+ | 4.9157 | 26.0 | 442 | 5.1273 |
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  | 4.8573 | 27.0 | 459 | 5.1273 |
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+ | 4.8307 | 28.0 | 476 | 5.1273 |
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  | 4.8523 | 29.0 | 493 | 5.1273 |
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+ | 4.8635 | 30.0 | 510 | 5.1273 |
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+ | 4.9477 | 31.0 | 527 | 5.1273 |
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+ | 4.9748 | 32.0 | 544 | 5.1273 |
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+ | 4.919 | 33.0 | 561 | 5.1273 |
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+ | 4.9646 | 34.0 | 578 | 5.1273 |
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+ | 4.906 | 35.0 | 595 | 5.1273 |
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+ | 4.8959 | 36.0 | 612 | 5.1273 |
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+ | 4.9289 | 37.0 | 629 | 5.1273 |
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+ | 4.9716 | 38.0 | 646 | 5.1273 |
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+ | 4.9264 | 39.0 | 663 | 5.1273 |
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+ | 4.9511 | 40.0 | 680 | 5.1273 |
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+ | 4.9559 | 41.0 | 697 | 5.1273 |
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+ | 4.8925 | 42.0 | 714 | 5.1273 |
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+ | 5.0009 | 43.0 | 731 | 5.1273 |
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+ | 5.0171 | 44.0 | 748 | 5.1273 |
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+ | 4.9922 | 45.0 | 765 | 5.1273 |
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+ | 4.9442 | 46.0 | 782 | 5.1273 |
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+ | 4.9718 | 47.0 | 799 | 5.1273 |
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  | 4.9723 | 48.0 | 816 | 5.1273 |
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  | 4.9641 | 49.0 | 833 | 5.1273 |
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+ | 4.9623 | 50.0 | 850 | 5.1273 |
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+ | 4.9661 | 51.0 | 867 | 5.1273 |
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+ | 4.9751 | 52.0 | 884 | 5.1273 |
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+ | 5.0271 | 53.0 | 901 | 5.1273 |
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+ | 5.0186 | 54.0 | 918 | 5.1273 |
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+ | 4.9842 | 55.0 | 935 | 5.1273 |
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  | 4.9846 | 56.0 | 952 | 5.1273 |
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+ | 5.0147 | 57.0 | 969 | 5.1273 |
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+ | 5.0593 | 58.0 | 986 | 5.1273 |
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  | 4.9787 | 59.0 | 1003 | 5.1273 |
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+ | 5.0569 | 60.0 | 1020 | 5.1273 |
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+ | 5.0237 | 61.0 | 1037 | 5.1273 |
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+ | 4.9641 | 62.0 | 1054 | 5.1273 |
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+ | 5.048 | 63.0 | 1071 | 5.1273 |
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+ | 4.9656 | 64.0 | 1088 | 5.1273 |
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+ | 5.0632 | 65.0 | 1105 | 5.1273 |
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+ | 5.0678 | 66.0 | 1122 | 5.1273 |
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+ | 5.0426 | 67.0 | 1139 | 5.1273 |
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+ | 5.0061 | 68.0 | 1156 | 5.1273 |
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+ | 4.9887 | 69.0 | 1173 | 5.1273 |
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+ | 5.0531 | 70.0 | 1190 | 5.1273 |
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+ | 5.1073 | 71.0 | 1207 | 5.1273 |
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  | 5.016 | 72.0 | 1224 | 5.1273 |
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+ | 5.0383 | 73.0 | 1241 | 5.1273 |
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  | 5.032 | 74.0 | 1258 | 5.1273 |
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+ | 5.0459 | 75.0 | 1275 | 5.1273 |
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  | 5.0734 | 76.0 | 1292 | 5.1273 |
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+ | 5.0059 | 77.0 | 1309 | 5.1273 |
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  | 5.027 | 78.0 | 1326 | 5.1273 |
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+ | 5.0383 | 79.0 | 1343 | 5.1273 |
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+ | 5.104 | 80.0 | 1360 | 5.1273 |
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  | 5.0209 | 81.0 | 1377 | 5.1273 |
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+ | 5.0443 | 82.0 | 1394 | 5.1273 |
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+ | 4.9923 | 83.0 | 1411 | 5.1273 |
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+ | 5.0462 | 84.0 | 1428 | 5.1273 |
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+ | 5.0416 | 85.0 | 1445 | 5.1273 |
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  | 5.0593 | 86.0 | 1462 | 5.1273 |
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+ | 5.1125 | 87.0 | 1479 | 5.1273 |
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  | 5.0125 | 88.0 | 1496 | 5.1273 |
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+ | 5.0925 | 89.0 | 1513 | 5.1273 |
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+ | 5.0681 | 90.0 | 1530 | 5.1273 |
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+ | 5.0962 | 91.0 | 1547 | 5.1273 |
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+ | 5.0843 | 92.0 | 1564 | 5.1273 |
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+ | 5.0987 | 93.0 | 1581 | 5.1273 |
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  | 5.0251 | 94.0 | 1598 | 5.1273 |
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+ | 5.0904 | 95.0 | 1615 | 5.1273 |
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+ | 5.1356 | 96.0 | 1632 | 5.1273 |
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  | 5.1103 | 97.0 | 1649 | 5.1273 |
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+ | 5.0244 | 98.0 | 1666 | 5.1273 |
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+ | 5.0914 | 99.0 | 1683 | 5.1273 |
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  | 5.1083 | 100.0 | 1700 | 5.1273 |
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