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update model card README.md

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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6845
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- - Accuracy: 0.5625
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  ## Model description
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@@ -43,163 +43,163 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_steps: 500
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  - num_epochs: 150
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 1 | 0.6980 | 0.375 |
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- | No log | 2.0 | 2 | 0.6980 | 0.375 |
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- | No log | 3.0 | 3 | 0.6980 | 0.375 |
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- | No log | 4.0 | 4 | 0.6979 | 0.375 |
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- | No log | 5.0 | 5 | 0.6978 | 0.375 |
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- | No log | 6.0 | 6 | 0.6978 | 0.4062 |
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- | No log | 7.0 | 7 | 0.6976 | 0.4062 |
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- | No log | 8.0 | 8 | 0.6975 | 0.4062 |
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- | No log | 9.0 | 9 | 0.6974 | 0.4062 |
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- | 0.6776 | 10.0 | 10 | 0.6972 | 0.4062 |
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- | 0.6776 | 11.0 | 11 | 0.6971 | 0.4062 |
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- | 0.6776 | 12.0 | 12 | 0.6969 | 0.4062 |
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- | 0.6776 | 13.0 | 13 | 0.6967 | 0.4062 |
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- | 0.6776 | 14.0 | 14 | 0.6964 | 0.4062 |
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- | 0.6776 | 15.0 | 15 | 0.6962 | 0.4062 |
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- | 0.6776 | 16.0 | 16 | 0.6959 | 0.4062 |
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- | 0.6776 | 17.0 | 17 | 0.6956 | 0.4062 |
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- | 0.6776 | 18.0 | 18 | 0.6953 | 0.4375 |
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- | 0.6776 | 19.0 | 19 | 0.6950 | 0.4375 |
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- | 0.6751 | 20.0 | 20 | 0.6947 | 0.4375 |
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- | 0.6751 | 21.0 | 21 | 0.6944 | 0.4688 |
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- | 0.6751 | 22.0 | 22 | 0.6941 | 0.4688 |
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- | 0.6751 | 23.0 | 23 | 0.6937 | 0.4688 |
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- | 0.6751 | 24.0 | 24 | 0.6933 | 0.4688 |
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- | 0.6751 | 25.0 | 25 | 0.6930 | 0.4688 |
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- | 0.6751 | 26.0 | 26 | 0.6926 | 0.5 |
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- | 0.6751 | 27.0 | 27 | 0.6923 | 0.5 |
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- | 0.6751 | 28.0 | 28 | 0.6920 | 0.5312 |
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- | 0.6751 | 29.0 | 29 | 0.6916 | 0.5312 |
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- | 0.6692 | 30.0 | 30 | 0.6913 | 0.5312 |
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- | 0.6692 | 31.0 | 31 | 0.6910 | 0.5312 |
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- | 0.6692 | 32.0 | 32 | 0.6906 | 0.5312 |
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- | 0.6692 | 33.0 | 33 | 0.6903 | 0.5312 |
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- | 0.6692 | 34.0 | 34 | 0.6899 | 0.5625 |
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- | 0.6692 | 35.0 | 35 | 0.6895 | 0.5625 |
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- | 0.6692 | 36.0 | 36 | 0.6891 | 0.5312 |
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- | 0.6692 | 37.0 | 37 | 0.6888 | 0.5312 |
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- | 0.6692 | 38.0 | 38 | 0.6884 | 0.5312 |
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- | 0.6692 | 39.0 | 39 | 0.6880 | 0.5 |
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- | 0.6502 | 40.0 | 40 | 0.6876 | 0.5 |
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- | 0.6502 | 41.0 | 41 | 0.6872 | 0.5 |
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- | 0.6502 | 42.0 | 42 | 0.6868 | 0.5 |
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- | 0.6502 | 43.0 | 43 | 0.6865 | 0.5 |
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- | 0.6502 | 44.0 | 44 | 0.6861 | 0.5 |
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- | 0.6502 | 45.0 | 45 | 0.6858 | 0.5312 |
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- | 0.6502 | 46.0 | 46 | 0.6854 | 0.5 |
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- | 0.6502 | 47.0 | 47 | 0.6851 | 0.5 |
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- | 0.6502 | 48.0 | 48 | 0.6848 | 0.5 |
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- | 0.6502 | 49.0 | 49 | 0.6844 | 0.5 |
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- | 0.6324 | 50.0 | 50 | 0.6841 | 0.5 |
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- | 0.6324 | 51.0 | 51 | 0.6837 | 0.5 |
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- | 0.6324 | 52.0 | 52 | 0.6834 | 0.5 |
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- | 0.6324 | 53.0 | 53 | 0.6831 | 0.5312 |
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- | 0.6324 | 54.0 | 54 | 0.6827 | 0.5 |
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- | 0.6324 | 55.0 | 55 | 0.6824 | 0.5312 |
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- | 0.6324 | 56.0 | 56 | 0.6820 | 0.5312 |
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- | 0.6324 | 57.0 | 57 | 0.6816 | 0.5312 |
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- | 0.6324 | 58.0 | 58 | 0.6813 | 0.5312 |
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- | 0.6324 | 59.0 | 59 | 0.6810 | 0.5625 |
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- | 0.5994 | 60.0 | 60 | 0.6806 | 0.5625 |
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- | 0.5994 | 61.0 | 61 | 0.6802 | 0.5625 |
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- | 0.5994 | 62.0 | 62 | 0.6798 | 0.5625 |
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- | 0.5994 | 63.0 | 63 | 0.6793 | 0.5625 |
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- | 0.5994 | 64.0 | 64 | 0.6789 | 0.5625 |
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- | 0.5994 | 65.0 | 65 | 0.6784 | 0.5625 |
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- | 0.5994 | 66.0 | 66 | 0.6779 | 0.5625 |
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- | 0.5994 | 67.0 | 67 | 0.6775 | 0.5625 |
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- | 0.5994 | 68.0 | 68 | 0.6770 | 0.5625 |
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- | 0.5994 | 69.0 | 69 | 0.6766 | 0.5625 |
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- | 0.5766 | 70.0 | 70 | 0.6761 | 0.5625 |
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- | 0.5766 | 71.0 | 71 | 0.6757 | 0.5625 |
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- | 0.5766 | 72.0 | 72 | 0.6752 | 0.5625 |
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- | 0.5766 | 73.0 | 73 | 0.6748 | 0.5625 |
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- | 0.5766 | 74.0 | 74 | 0.6744 | 0.5625 |
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- | 0.5766 | 75.0 | 75 | 0.6740 | 0.5625 |
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- | 0.5766 | 76.0 | 76 | 0.6736 | 0.5625 |
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- | 0.5766 | 77.0 | 77 | 0.6731 | 0.5625 |
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- | 0.5766 | 78.0 | 78 | 0.6726 | 0.5625 |
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- | 0.5766 | 79.0 | 79 | 0.6719 | 0.5625 |
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- | 0.5315 | 80.0 | 80 | 0.6712 | 0.5625 |
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- | 0.5315 | 81.0 | 81 | 0.6704 | 0.5625 |
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- | 0.5315 | 82.0 | 82 | 0.6695 | 0.5625 |
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- | 0.5315 | 83.0 | 83 | 0.6686 | 0.5625 |
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- | 0.5315 | 84.0 | 84 | 0.6676 | 0.5625 |
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- | 0.5315 | 85.0 | 85 | 0.6667 | 0.5625 |
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- | 0.5315 | 86.0 | 86 | 0.6658 | 0.5625 |
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- | 0.5315 | 87.0 | 87 | 0.6650 | 0.5625 |
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- | 0.5315 | 88.0 | 88 | 0.6642 | 0.5625 |
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- | 0.5315 | 89.0 | 89 | 0.6635 | 0.5625 |
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- | 0.4899 | 90.0 | 90 | 0.6628 | 0.5625 |
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- | 0.4899 | 91.0 | 91 | 0.6623 | 0.5625 |
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- | 0.4899 | 92.0 | 92 | 0.6617 | 0.5625 |
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- | 0.4899 | 93.0 | 93 | 0.6613 | 0.5625 |
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- | 0.4899 | 94.0 | 94 | 0.6612 | 0.5625 |
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- | 0.4899 | 95.0 | 95 | 0.6611 | 0.5625 |
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- | 0.4899 | 96.0 | 96 | 0.6612 | 0.5625 |
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- | 0.4899 | 97.0 | 97 | 0.6616 | 0.5625 |
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- | 0.4899 | 98.0 | 98 | 0.6622 | 0.5625 |
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- | 0.4899 | 99.0 | 99 | 0.6630 | 0.5625 |
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- | 0.4457 | 100.0 | 100 | 0.6641 | 0.5625 |
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- | 0.4457 | 101.0 | 101 | 0.6652 | 0.5625 |
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- | 0.4457 | 102.0 | 102 | 0.6663 | 0.5938 |
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- | 0.4457 | 103.0 | 103 | 0.6665 | 0.5938 |
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- | 0.4457 | 104.0 | 104 | 0.6653 | 0.5938 |
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- | 0.4457 | 105.0 | 105 | 0.6643 | 0.5938 |
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- | 0.4457 | 106.0 | 106 | 0.6642 | 0.5625 |
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- | 0.4457 | 107.0 | 107 | 0.6648 | 0.5625 |
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- | 0.4457 | 108.0 | 108 | 0.6657 | 0.5625 |
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- | 0.4457 | 109.0 | 109 | 0.6662 | 0.5625 |
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- | 0.3877 | 110.0 | 110 | 0.6664 | 0.5625 |
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- | 0.3877 | 111.0 | 111 | 0.6666 | 0.5625 |
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- | 0.3877 | 112.0 | 112 | 0.6669 | 0.5625 |
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- | 0.3877 | 113.0 | 113 | 0.6673 | 0.5625 |
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- | 0.3877 | 114.0 | 114 | 0.6677 | 0.5625 |
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- | 0.3877 | 115.0 | 115 | 0.6684 | 0.5625 |
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- | 0.3877 | 116.0 | 116 | 0.6692 | 0.5625 |
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- | 0.3877 | 117.0 | 117 | 0.6697 | 0.5625 |
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- | 0.3877 | 118.0 | 118 | 0.6703 | 0.5625 |
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- | 0.3877 | 119.0 | 119 | 0.6710 | 0.5625 |
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- | 0.3428 | 120.0 | 120 | 0.6716 | 0.5625 |
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- | 0.3428 | 121.0 | 121 | 0.6722 | 0.5625 |
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- | 0.3428 | 122.0 | 122 | 0.6729 | 0.5625 |
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- | 0.3428 | 123.0 | 123 | 0.6735 | 0.5625 |
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- | 0.3428 | 124.0 | 124 | 0.6741 | 0.5625 |
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- | 0.3428 | 125.0 | 125 | 0.6745 | 0.5625 |
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- | 0.3428 | 126.0 | 126 | 0.6748 | 0.5625 |
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- | 0.3428 | 127.0 | 127 | 0.6750 | 0.5625 |
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- | 0.3428 | 128.0 | 128 | 0.6751 | 0.5625 |
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- | 0.3428 | 129.0 | 129 | 0.6749 | 0.5625 |
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- | 0.3212 | 130.0 | 130 | 0.6747 | 0.5625 |
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- | 0.3212 | 131.0 | 131 | 0.6746 | 0.5625 |
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- | 0.3212 | 132.0 | 132 | 0.6746 | 0.5625 |
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- | 0.3212 | 133.0 | 133 | 0.6744 | 0.5625 |
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- | 0.3212 | 134.0 | 134 | 0.6742 | 0.5625 |
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- | 0.3212 | 135.0 | 135 | 0.6740 | 0.5625 |
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- | 0.3212 | 136.0 | 136 | 0.6739 | 0.5625 |
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- | 0.3212 | 137.0 | 137 | 0.6735 | 0.5625 |
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- | 0.3212 | 138.0 | 138 | 0.6735 | 0.5625 |
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- | 0.3212 | 139.0 | 139 | 0.6738 | 0.5625 |
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- | 0.2766 | 140.0 | 140 | 0.6745 | 0.5625 |
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- | 0.2766 | 141.0 | 141 | 0.6753 | 0.5625 |
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- | 0.2766 | 142.0 | 142 | 0.6761 | 0.5625 |
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- | 0.2766 | 143.0 | 143 | 0.6772 | 0.5625 |
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- | 0.2766 | 144.0 | 144 | 0.6784 | 0.5625 |
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- | 0.2766 | 145.0 | 145 | 0.6799 | 0.5625 |
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- | 0.2766 | 146.0 | 146 | 0.6815 | 0.5625 |
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- | 0.2766 | 147.0 | 147 | 0.6827 | 0.5625 |
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- | 0.2766 | 148.0 | 148 | 0.6837 | 0.5625 |
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- | 0.2766 | 149.0 | 149 | 0.6842 | 0.5625 |
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- | 0.2476 | 150.0 | 150 | 0.6845 | 0.5625 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5049
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+ - Accuracy: 0.8125
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 50
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  - num_epochs: 150
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 1 | 0.7051 | 0.5312 |
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+ | No log | 2.0 | 2 | 0.7048 | 0.5312 |
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+ | No log | 3.0 | 3 | 0.7041 | 0.5312 |
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+ | No log | 4.0 | 4 | 0.7029 | 0.5312 |
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+ | No log | 5.0 | 5 | 0.7014 | 0.5625 |
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+ | No log | 6.0 | 6 | 0.6996 | 0.5625 |
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+ | No log | 7.0 | 7 | 0.6975 | 0.5625 |
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+ | No log | 8.0 | 8 | 0.6951 | 0.5625 |
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+ | No log | 9.0 | 9 | 0.6922 | 0.5625 |
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+ | 0.7427 | 10.0 | 10 | 0.6891 | 0.5625 |
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+ | 0.7427 | 11.0 | 11 | 0.6857 | 0.5625 |
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+ | 0.7427 | 12.0 | 12 | 0.6820 | 0.5625 |
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+ | 0.7427 | 13.0 | 13 | 0.6781 | 0.5625 |
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+ | 0.7427 | 14.0 | 14 | 0.6740 | 0.5625 |
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+ | 0.7427 | 15.0 | 15 | 0.6698 | 0.5312 |
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+ | 0.7427 | 16.0 | 16 | 0.6658 | 0.5938 |
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+ | 0.7427 | 17.0 | 17 | 0.6621 | 0.5625 |
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+ | 0.7427 | 18.0 | 18 | 0.6585 | 0.5625 |
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+ | 0.7427 | 19.0 | 19 | 0.6550 | 0.6562 |
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+ | 0.6663 | 20.0 | 20 | 0.6516 | 0.6562 |
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+ | 0.6663 | 21.0 | 21 | 0.6489 | 0.7188 |
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+ | 0.6663 | 22.0 | 22 | 0.6471 | 0.7188 |
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+ | 0.6663 | 23.0 | 23 | 0.6465 | 0.75 |
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+ | 0.6663 | 24.0 | 24 | 0.6465 | 0.75 |
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+ | 0.6663 | 25.0 | 25 | 0.6461 | 0.7188 |
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+ | 0.6663 | 26.0 | 26 | 0.6450 | 0.7188 |
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+ | 0.6663 | 27.0 | 27 | 0.6427 | 0.6875 |
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+ | 0.6663 | 28.0 | 28 | 0.6394 | 0.6875 |
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+ | 0.6663 | 29.0 | 29 | 0.6358 | 0.7188 |
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+ | 0.5394 | 30.0 | 30 | 0.6319 | 0.75 |
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+ | 0.5394 | 31.0 | 31 | 0.6279 | 0.75 |
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+ | 0.5394 | 32.0 | 32 | 0.6244 | 0.7812 |
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+ | 0.5394 | 33.0 | 33 | 0.6207 | 0.7812 |
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+ | 0.5394 | 34.0 | 34 | 0.6169 | 0.7812 |
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+ | 0.5394 | 35.0 | 35 | 0.6131 | 0.7812 |
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+ | 0.5394 | 36.0 | 36 | 0.6096 | 0.7812 |
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+ | 0.5394 | 37.0 | 37 | 0.6057 | 0.7812 |
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+ | 0.5394 | 38.0 | 38 | 0.6028 | 0.7812 |
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+ | 0.5394 | 39.0 | 39 | 0.6010 | 0.75 |
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+ | 0.3922 | 40.0 | 40 | 0.5975 | 0.75 |
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+ | 0.3922 | 41.0 | 41 | 0.5941 | 0.75 |
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+ | 0.3922 | 42.0 | 42 | 0.5902 | 0.75 |
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+ | 0.3922 | 43.0 | 43 | 0.5854 | 0.75 |
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+ | 0.3922 | 44.0 | 44 | 0.5800 | 0.75 |
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+ | 0.3922 | 45.0 | 45 | 0.5768 | 0.7188 |
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+ | 0.3922 | 46.0 | 46 | 0.5747 | 0.7188 |
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+ | 0.3922 | 47.0 | 47 | 0.5743 | 0.7188 |
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+ | 0.3922 | 48.0 | 48 | 0.5765 | 0.7188 |
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+ | 0.3922 | 49.0 | 49 | 0.5779 | 0.6875 |
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+ | 0.2715 | 50.0 | 50 | 0.5813 | 0.7188 |
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+ | 0.2715 | 51.0 | 51 | 0.5839 | 0.6875 |
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+ | 0.2715 | 52.0 | 52 | 0.5857 | 0.7188 |
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+ | 0.2715 | 53.0 | 53 | 0.5916 | 0.7188 |
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+ | 0.2715 | 54.0 | 54 | 0.5986 | 0.75 |
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+ | 0.2715 | 55.0 | 55 | 0.6033 | 0.75 |
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+ | 0.2715 | 56.0 | 56 | 0.6016 | 0.75 |
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+ | 0.2715 | 57.0 | 57 | 0.6004 | 0.75 |
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+ | 0.2715 | 58.0 | 58 | 0.5928 | 0.75 |
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+ | 0.2715 | 59.0 | 59 | 0.5860 | 0.7812 |
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+ | 0.174 | 60.0 | 60 | 0.5795 | 0.75 |
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+ | 0.174 | 61.0 | 61 | 0.5707 | 0.75 |
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+ | 0.174 | 62.0 | 62 | 0.5629 | 0.7188 |
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+ | 0.174 | 63.0 | 63 | 0.5578 | 0.6875 |
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+ | 0.174 | 64.0 | 64 | 0.5535 | 0.7188 |
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+ | 0.174 | 65.0 | 65 | 0.5498 | 0.7188 |
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+ | 0.174 | 66.0 | 66 | 0.5468 | 0.7188 |
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+ | 0.174 | 67.0 | 67 | 0.5436 | 0.7188 |
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+ | 0.174 | 68.0 | 68 | 0.5404 | 0.7188 |
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+ | 0.174 | 69.0 | 69 | 0.5373 | 0.7188 |
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+ | 0.1107 | 70.0 | 70 | 0.5353 | 0.7188 |
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+ | 0.1107 | 71.0 | 71 | 0.5327 | 0.7188 |
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+ | 0.1107 | 72.0 | 72 | 0.5292 | 0.7188 |
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+ | 0.1107 | 73.0 | 73 | 0.5243 | 0.75 |
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+ | 0.1107 | 74.0 | 74 | 0.5187 | 0.75 |
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+ | 0.1107 | 75.0 | 75 | 0.5131 | 0.75 |
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+ | 0.1107 | 76.0 | 76 | 0.5081 | 0.75 |
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+ | 0.1107 | 77.0 | 77 | 0.5036 | 0.75 |
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+ | 0.1107 | 78.0 | 78 | 0.5005 | 0.75 |
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+ | 0.1107 | 79.0 | 79 | 0.4982 | 0.7812 |
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+ | 0.0742 | 80.0 | 80 | 0.4970 | 0.8438 |
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+ | 0.0742 | 81.0 | 81 | 0.4958 | 0.8438 |
134
+ | 0.0742 | 82.0 | 82 | 0.4939 | 0.8438 |
135
+ | 0.0742 | 83.0 | 83 | 0.4908 | 0.8438 |
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+ | 0.0742 | 84.0 | 84 | 0.4873 | 0.8125 |
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+ | 0.0742 | 85.0 | 85 | 0.4840 | 0.8125 |
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+ | 0.0742 | 86.0 | 86 | 0.4814 | 0.8125 |
139
+ | 0.0742 | 87.0 | 87 | 0.4790 | 0.8125 |
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+ | 0.0742 | 88.0 | 88 | 0.4769 | 0.8125 |
141
+ | 0.0742 | 89.0 | 89 | 0.4750 | 0.8125 |
142
+ | 0.0494 | 90.0 | 90 | 0.4742 | 0.8125 |
143
+ | 0.0494 | 91.0 | 91 | 0.4737 | 0.8125 |
144
+ | 0.0494 | 92.0 | 92 | 0.4731 | 0.8125 |
145
+ | 0.0494 | 93.0 | 93 | 0.4726 | 0.8125 |
146
+ | 0.0494 | 94.0 | 94 | 0.4722 | 0.8125 |
147
+ | 0.0494 | 95.0 | 95 | 0.4720 | 0.8125 |
148
+ | 0.0494 | 96.0 | 96 | 0.4720 | 0.8125 |
149
+ | 0.0494 | 97.0 | 97 | 0.4715 | 0.8125 |
150
+ | 0.0494 | 98.0 | 98 | 0.4712 | 0.8125 |
151
+ | 0.0494 | 99.0 | 99 | 0.4710 | 0.8125 |
152
+ | 0.0331 | 100.0 | 100 | 0.4709 | 0.8125 |
153
+ | 0.0331 | 101.0 | 101 | 0.4711 | 0.8125 |
154
+ | 0.0331 | 102.0 | 102 | 0.4715 | 0.8125 |
155
+ | 0.0331 | 103.0 | 103 | 0.4725 | 0.8125 |
156
+ | 0.0331 | 104.0 | 104 | 0.4734 | 0.8125 |
157
+ | 0.0331 | 105.0 | 105 | 0.4742 | 0.8125 |
158
+ | 0.0331 | 106.0 | 106 | 0.4752 | 0.8125 |
159
+ | 0.0331 | 107.0 | 107 | 0.4761 | 0.8125 |
160
+ | 0.0331 | 108.0 | 108 | 0.4770 | 0.8125 |
161
+ | 0.0331 | 109.0 | 109 | 0.4780 | 0.8125 |
162
+ | 0.0246 | 110.0 | 110 | 0.4789 | 0.8125 |
163
+ | 0.0246 | 111.0 | 111 | 0.4804 | 0.8125 |
164
+ | 0.0246 | 112.0 | 112 | 0.4817 | 0.8125 |
165
+ | 0.0246 | 113.0 | 113 | 0.4829 | 0.8125 |
166
+ | 0.0246 | 114.0 | 114 | 0.4842 | 0.8125 |
167
+ | 0.0246 | 115.0 | 115 | 0.4851 | 0.8125 |
168
+ | 0.0246 | 116.0 | 116 | 0.4863 | 0.8125 |
169
+ | 0.0246 | 117.0 | 117 | 0.4880 | 0.8125 |
170
+ | 0.0246 | 118.0 | 118 | 0.4897 | 0.8125 |
171
+ | 0.0246 | 119.0 | 119 | 0.4913 | 0.8125 |
172
+ | 0.0191 | 120.0 | 120 | 0.4930 | 0.8125 |
173
+ | 0.0191 | 121.0 | 121 | 0.4945 | 0.8125 |
174
+ | 0.0191 | 122.0 | 122 | 0.4959 | 0.8125 |
175
+ | 0.0191 | 123.0 | 123 | 0.4971 | 0.8125 |
176
+ | 0.0191 | 124.0 | 124 | 0.4984 | 0.8125 |
177
+ | 0.0191 | 125.0 | 125 | 0.4995 | 0.8125 |
178
+ | 0.0191 | 126.0 | 126 | 0.5004 | 0.8125 |
179
+ | 0.0191 | 127.0 | 127 | 0.5014 | 0.8125 |
180
+ | 0.0191 | 128.0 | 128 | 0.5021 | 0.8125 |
181
+ | 0.0191 | 129.0 | 129 | 0.5027 | 0.8125 |
182
+ | 0.0163 | 130.0 | 130 | 0.5031 | 0.8125 |
183
+ | 0.0163 | 131.0 | 131 | 0.5031 | 0.8125 |
184
+ | 0.0163 | 132.0 | 132 | 0.5034 | 0.8125 |
185
+ | 0.0163 | 133.0 | 133 | 0.5035 | 0.8125 |
186
+ | 0.0163 | 134.0 | 134 | 0.5036 | 0.8125 |
187
+ | 0.0163 | 135.0 | 135 | 0.5036 | 0.8125 |
188
+ | 0.0163 | 136.0 | 136 | 0.5037 | 0.8125 |
189
+ | 0.0163 | 137.0 | 137 | 0.5038 | 0.8125 |
190
+ | 0.0163 | 138.0 | 138 | 0.5040 | 0.8125 |
191
+ | 0.0163 | 139.0 | 139 | 0.5043 | 0.8125 |
192
+ | 0.0147 | 140.0 | 140 | 0.5044 | 0.8125 |
193
+ | 0.0147 | 141.0 | 141 | 0.5046 | 0.8125 |
194
+ | 0.0147 | 142.0 | 142 | 0.5047 | 0.8125 |
195
+ | 0.0147 | 143.0 | 143 | 0.5049 | 0.8125 |
196
+ | 0.0147 | 144.0 | 144 | 0.5049 | 0.8125 |
197
+ | 0.0147 | 145.0 | 145 | 0.5049 | 0.8125 |
198
+ | 0.0147 | 146.0 | 146 | 0.5049 | 0.8125 |
199
+ | 0.0147 | 147.0 | 147 | 0.5049 | 0.8125 |
200
+ | 0.0147 | 148.0 | 148 | 0.5049 | 0.8125 |
201
+ | 0.0147 | 149.0 | 149 | 0.5049 | 0.8125 |
202
+ | 0.0138 | 150.0 | 150 | 0.5049 | 0.8125 |
203
 
204
 
205
  ### Framework versions