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qa_model

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Safetensors
distilbert
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  1. README.md +102 -102
  2. model.safetensors +1 -1
  3. runs/Apr15_23-27-20_asrlytics-server/events.out.tfevents.1713203845.asrlytics-server.42534.0 +2 -2
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0785
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  ## Model description
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@@ -34,7 +34,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -46,106 +46,106 @@ 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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- | No log | 1.0 | 14 | 0.1091 |
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- | No log | 2.0 | 28 | 0.1130 |
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- | No log | 3.0 | 42 | 0.1122 |
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- | No log | 4.0 | 56 | 0.1073 |
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- | No log | 5.0 | 70 | 0.0929 |
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- | No log | 6.0 | 84 | 0.0910 |
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- | No log | 7.0 | 98 | 0.0926 |
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- | No log | 8.0 | 112 | 0.1022 |
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- | No log | 9.0 | 126 | 0.0937 |
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- | No log | 10.0 | 140 | 0.0975 |
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- | No log | 11.0 | 154 | 0.0950 |
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- | No log | 12.0 | 168 | 0.1064 |
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- | No log | 13.0 | 182 | 0.1137 |
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- | No log | 14.0 | 196 | 0.0951 |
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- | No log | 15.0 | 210 | 0.1074 |
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- | No log | 16.0 | 224 | 0.1007 |
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- | No log | 17.0 | 238 | 0.0919 |
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- | No log | 18.0 | 252 | 0.0859 |
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- | No log | 19.0 | 266 | 0.1020 |
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- | No log | 20.0 | 280 | 0.0830 |
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- | No log | 21.0 | 294 | 0.0839 |
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- | No log | 22.0 | 308 | 0.0834 |
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- | No log | 23.0 | 322 | 0.0824 |
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- | No log | 24.0 | 336 | 0.0837 |
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- | No log | 25.0 | 350 | 0.0915 |
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- | No log | 26.0 | 364 | 0.0918 |
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- | No log | 27.0 | 378 | 0.0827 |
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- | No log | 28.0 | 392 | 0.0824 |
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- | No log | 29.0 | 406 | 0.0816 |
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- | No log | 30.0 | 420 | 0.0904 |
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- | No log | 31.0 | 434 | 0.0872 |
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- | No log | 32.0 | 448 | 0.0810 |
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- | No log | 33.0 | 462 | 0.0817 |
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- | No log | 34.0 | 476 | 0.0841 |
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- | No log | 35.0 | 490 | 0.0826 |
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- | 0.1061 | 36.0 | 504 | 0.0847 |
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- | 0.1061 | 37.0 | 518 | 0.0830 |
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- | 0.1061 | 38.0 | 532 | 0.0817 |
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- | 0.1061 | 39.0 | 546 | 0.0833 |
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- | 0.1061 | 40.0 | 560 | 0.0810 |
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- | 0.1061 | 41.0 | 574 | 0.0859 |
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- | 0.1061 | 42.0 | 588 | 0.0811 |
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- | 0.1061 | 43.0 | 602 | 0.0802 |
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- | 0.1061 | 44.0 | 616 | 0.0807 |
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- | 0.1061 | 45.0 | 630 | 0.0806 |
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- | 0.1061 | 46.0 | 644 | 0.0809 |
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- | 0.1061 | 47.0 | 658 | 0.0800 |
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- | 0.1061 | 48.0 | 672 | 0.0793 |
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- | 0.1061 | 49.0 | 686 | 0.0801 |
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- | 0.1061 | 50.0 | 700 | 0.0794 |
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- | 0.1061 | 51.0 | 714 | 0.0836 |
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- | 0.1061 | 52.0 | 728 | 0.0813 |
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- | 0.1061 | 53.0 | 742 | 0.0803 |
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- | 0.1061 | 54.0 | 756 | 0.0791 |
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- | 0.1061 | 55.0 | 770 | 0.0798 |
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- | 0.1061 | 56.0 | 784 | 0.0811 |
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- | 0.1061 | 57.0 | 798 | 0.0811 |
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- | 0.1061 | 58.0 | 812 | 0.0801 |
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- | 0.1061 | 59.0 | 826 | 0.0800 |
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- | 0.1061 | 60.0 | 840 | 0.0795 |
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- | 0.1061 | 61.0 | 854 | 0.0796 |
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- | 0.1061 | 62.0 | 868 | 0.0796 |
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- | 0.1061 | 63.0 | 882 | 0.0799 |
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- | 0.1061 | 64.0 | 896 | 0.0793 |
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- | 0.1061 | 65.0 | 910 | 0.0791 |
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- | 0.1061 | 66.0 | 924 | 0.0790 |
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- | 0.1061 | 67.0 | 938 | 0.0790 |
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- | 0.1061 | 68.0 | 952 | 0.0789 |
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- | 0.1061 | 69.0 | 966 | 0.0790 |
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- | 0.1061 | 70.0 | 980 | 0.0790 |
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- | 0.1061 | 71.0 | 994 | 0.0789 |
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- | 0.088 | 72.0 | 1008 | 0.0789 |
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- | 0.088 | 73.0 | 1022 | 0.0789 |
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- | 0.088 | 74.0 | 1036 | 0.0788 |
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- | 0.088 | 75.0 | 1050 | 0.0788 |
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- | 0.088 | 76.0 | 1064 | 0.0788 |
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- | 0.088 | 77.0 | 1078 | 0.0787 |
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- | 0.088 | 78.0 | 1092 | 0.0787 |
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- | 0.088 | 79.0 | 1106 | 0.0787 |
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- | 0.088 | 80.0 | 1120 | 0.0786 |
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- | 0.088 | 81.0 | 1134 | 0.0787 |
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- | 0.088 | 82.0 | 1148 | 0.0790 |
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- | 0.088 | 83.0 | 1162 | 0.0787 |
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- | 0.088 | 84.0 | 1176 | 0.0787 |
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- | 0.088 | 85.0 | 1190 | 0.0787 |
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- | 0.088 | 86.0 | 1204 | 0.0787 |
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- | 0.088 | 87.0 | 1218 | 0.0789 |
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- | 0.088 | 88.0 | 1232 | 0.0789 |
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- | 0.088 | 89.0 | 1246 | 0.0789 |
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- | 0.088 | 90.0 | 1260 | 0.0788 |
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- | 0.088 | 91.0 | 1274 | 0.0788 |
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- | 0.088 | 92.0 | 1288 | 0.0786 |
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- | 0.088 | 93.0 | 1302 | 0.0786 |
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- | 0.088 | 94.0 | 1316 | 0.0785 |
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- | 0.088 | 95.0 | 1330 | 0.0785 |
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- | 0.088 | 96.0 | 1344 | 0.0785 |
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- | 0.088 | 97.0 | 1358 | 0.0785 |
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- | 0.088 | 98.0 | 1372 | 0.0785 |
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- | 0.088 | 99.0 | 1386 | 0.0785 |
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- | 0.088 | 100.0 | 1400 | 0.0785 |
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  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 0.0737
19
 
20
  ## Model description
21
 
 
34
  ### Training hyperparameters
35
 
36
  The following hyperparameters were used during training:
37
+ - learning_rate: 2e-05
38
  - train_batch_size: 16
39
  - eval_batch_size: 16
40
  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss |
48
  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 14 | 3.6840 |
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+ | No log | 2.0 | 28 | 1.5996 |
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+ | No log | 3.0 | 42 | 0.9961 |
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+ | No log | 4.0 | 56 | 0.7927 |
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+ | No log | 5.0 | 70 | 0.6597 |
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+ | No log | 6.0 | 84 | 0.5352 |
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+ | No log | 7.0 | 98 | 0.4412 |
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+ | No log | 8.0 | 112 | 0.3435 |
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+ | No log | 9.0 | 126 | 0.2955 |
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+ | No log | 10.0 | 140 | 0.2741 |
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+ | No log | 11.0 | 154 | 0.2211 |
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+ | No log | 12.0 | 168 | 0.1959 |
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+ | No log | 13.0 | 182 | 0.1783 |
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+ | No log | 14.0 | 196 | 0.1919 |
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+ | No log | 15.0 | 210 | 0.1640 |
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+ | No log | 16.0 | 224 | 0.1439 |
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+ | No log | 17.0 | 238 | 0.1479 |
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+ | No log | 18.0 | 252 | 0.1536 |
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+ | No log | 19.0 | 266 | 0.1365 |
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+ | No log | 20.0 | 280 | 0.1444 |
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+ | No log | 21.0 | 294 | 0.1268 |
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+ | No log | 22.0 | 308 | 0.1330 |
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+ | No log | 23.0 | 322 | 0.1192 |
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+ | No log | 24.0 | 336 | 0.1254 |
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+ | No log | 25.0 | 350 | 0.1168 |
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+ | No log | 26.0 | 364 | 0.1099 |
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+ | No log | 27.0 | 378 | 0.1077 |
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+ | No log | 28.0 | 392 | 0.1134 |
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+ | No log | 29.0 | 406 | 0.1039 |
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+ | No log | 30.0 | 420 | 0.1293 |
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+ | No log | 31.0 | 434 | 0.1211 |
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+ | No log | 32.0 | 448 | 0.0997 |
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+ | No log | 33.0 | 462 | 0.1052 |
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+ | No log | 34.0 | 476 | 0.1067 |
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+ | No log | 35.0 | 490 | 0.0974 |
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+ | 0.5014 | 36.0 | 504 | 0.0987 |
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+ | 0.5014 | 37.0 | 518 | 0.0955 |
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+ | 0.5014 | 38.0 | 532 | 0.0938 |
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+ | 0.5014 | 39.0 | 546 | 0.0894 |
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+ | 0.5014 | 40.0 | 560 | 0.0873 |
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+ | 0.5014 | 41.0 | 574 | 0.0943 |
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+ | 0.5014 | 42.0 | 588 | 0.0917 |
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+ | 0.5014 | 43.0 | 602 | 0.0869 |
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+ | 0.5014 | 44.0 | 616 | 0.0896 |
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+ | 0.5014 | 45.0 | 630 | 0.0857 |
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+ | 0.5014 | 46.0 | 644 | 0.0889 |
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+ | 0.5014 | 47.0 | 658 | 0.0854 |
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+ | 0.5014 | 48.0 | 672 | 0.0896 |
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+ | 0.5014 | 49.0 | 686 | 0.0848 |
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+ | 0.5014 | 50.0 | 700 | 0.0882 |
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+ | 0.5014 | 51.0 | 714 | 0.0840 |
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+ | 0.5014 | 52.0 | 728 | 0.0826 |
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+ | 0.5014 | 53.0 | 742 | 0.0843 |
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+ | 0.5014 | 54.0 | 756 | 0.0823 |
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+ | 0.5014 | 55.0 | 770 | 0.0805 |
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+ | 0.5014 | 56.0 | 784 | 0.0799 |
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+ | 0.5014 | 57.0 | 798 | 0.0776 |
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+ | 0.5014 | 58.0 | 812 | 0.0775 |
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+ | 0.5014 | 59.0 | 826 | 0.0776 |
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+ | 0.5014 | 60.0 | 840 | 0.0761 |
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+ | 0.5014 | 61.0 | 854 | 0.0756 |
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+ | 0.5014 | 62.0 | 868 | 0.0764 |
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+ | 0.5014 | 63.0 | 882 | 0.0768 |
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+ | 0.5014 | 64.0 | 896 | 0.0764 |
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+ | 0.5014 | 65.0 | 910 | 0.0770 |
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+ | 0.5014 | 66.0 | 924 | 0.0766 |
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+ | 0.5014 | 67.0 | 938 | 0.0776 |
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+ | 0.5014 | 68.0 | 952 | 0.0752 |
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+ | 0.5014 | 69.0 | 966 | 0.0762 |
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+ | 0.5014 | 70.0 | 980 | 0.0764 |
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+ | 0.5014 | 71.0 | 994 | 0.0747 |
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+ | 0.0961 | 72.0 | 1008 | 0.0762 |
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+ | 0.0961 | 73.0 | 1022 | 0.0767 |
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+ | 0.0961 | 74.0 | 1036 | 0.0766 |
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+ | 0.0961 | 75.0 | 1050 | 0.0767 |
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+ | 0.0961 | 76.0 | 1064 | 0.0755 |
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+ | 0.0961 | 77.0 | 1078 | 0.0755 |
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+ | 0.0961 | 78.0 | 1092 | 0.0751 |
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+ | 0.0961 | 79.0 | 1106 | 0.0747 |
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+ | 0.0961 | 80.0 | 1120 | 0.0756 |
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+ | 0.0961 | 81.0 | 1134 | 0.0752 |
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+ | 0.0961 | 82.0 | 1148 | 0.0751 |
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+ | 0.0961 | 83.0 | 1162 | 0.0749 |
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+ | 0.0961 | 84.0 | 1176 | 0.0748 |
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+ | 0.0961 | 85.0 | 1190 | 0.0744 |
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+ | 0.0961 | 86.0 | 1204 | 0.0742 |
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+ | 0.0961 | 87.0 | 1218 | 0.0747 |
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+ | 0.0961 | 88.0 | 1232 | 0.0745 |
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+ | 0.0961 | 89.0 | 1246 | 0.0739 |
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+ | 0.0961 | 90.0 | 1260 | 0.0738 |
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+ | 0.0961 | 91.0 | 1274 | 0.0739 |
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+ | 0.0961 | 92.0 | 1288 | 0.0740 |
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+ | 0.0961 | 93.0 | 1302 | 0.0738 |
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+ | 0.0961 | 94.0 | 1316 | 0.0738 |
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+ | 0.0961 | 95.0 | 1330 | 0.0737 |
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+ | 0.0961 | 96.0 | 1344 | 0.0736 |
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+ | 0.0961 | 97.0 | 1358 | 0.0737 |
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+ | 0.0961 | 98.0 | 1372 | 0.0737 |
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+ | 0.0961 | 99.0 | 1386 | 0.0737 |
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+ | 0.0961 | 100.0 | 1400 | 0.0737 |
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  ### Framework versions
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