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MJ199999
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gpt3_model

Text Generation
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TensorFlow
gpt2
generated_from_keras_callback
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add model

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  1. README.md +504 -204
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -13,9 +13,9 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MJ199999/gpt3_model](https://huggingface.co/MJ199999/gpt3_model) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.4635
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- - Train Lr: 9.999999e-05
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- - Epoch: 199
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  ## Model description
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@@ -34,213 +34,513 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - optimizer: {'name': 'Adagrad', 'learning_rate': 9.999999e-05, 'decay': 0.0, 'initial_accumulator_value': 0.1, 'epsilon': 1e-07}
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  - training_precision: float32
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  ### Training results
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  | Train Loss | Train Lr | Epoch |
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  |:----------:|:------------:|:-----:|
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- | 5.9839 | 0.01 | 0 |
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- | 5.3590 | 0.01 | 1 |
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- | 4.8662 | 0.01 | 2 |
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- | 4.2878 | 0.01 | 3 |
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- | 3.6482 | 0.01 | 4 |
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- | 3.0220 | 0.01 | 5 |
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- | 2.5057 | 0.01 | 6 |
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- | 2.1530 | 0.01 | 7 |
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- | 1.8817 | 0.01 | 8 |
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- | 1.6666 | 0.01 | 9 |
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- | 1.5034 | 0.01 | 10 |
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- | 1.3592 | 0.01 | 11 |
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- | 1.2743 | 0.01 | 12 |
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- | 1.1953 | 0.01 | 13 |
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- | 1.1265 | 0.01 | 14 |
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- | 1.0642 | 0.01 | 15 |
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- | 1.0352 | 0.01 | 16 |
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- | 0.9863 | 0.01 | 17 |
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- | 0.9612 | 0.01 | 18 |
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- | 0.9259 | 0.01 | 19 |
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- | 0.9051 | 0.01 | 20 |
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- | 0.8740 | 0.01 | 21 |
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- | 0.8529 | 0.01 | 22 |
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- | 0.8360 | 0.01 | 23 |
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- | 0.8209 | 0.01 | 24 |
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- | 0.8083 | 0.01 | 25 |
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- | 0.7941 | 0.01 | 26 |
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- | 0.7916 | 0.01 | 27 |
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- | 0.7688 | 0.01 | 28 |
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- | 0.7597 | 0.01 | 29 |
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- | 0.7603 | 0.01 | 30 |
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- | 0.7446 | 0.01 | 31 |
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- | 0.7324 | 0.01 | 32 |
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- | 0.7274 | 0.01 | 33 |
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- | 0.7141 | 0.01 | 34 |
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- | 0.7124 | 0.01 | 35 |
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- | 0.7075 | 0.01 | 36 |
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- | 0.7004 | 0.01 | 37 |
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- | 0.6949 | 0.01 | 38 |
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- | 0.6931 | 0.01 | 39 |
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- | 0.6841 | 0.01 | 40 |
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- | 0.6827 | 0.01 | 41 |
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- | 0.6889 | 0.01 | 42 |
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- | 0.6760 | 0.01 | 43 |
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- | 0.6752 | 0.01 | 44 |
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- | 0.6692 | 0.01 | 45 |
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- | 0.6636 | 0.01 | 46 |
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- | 0.6556 | 0.01 | 47 |
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- | 0.6486 | 0.01 | 48 |
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- | 0.6441 | 0.01 | 49 |
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- | 0.6493 | 0.01 | 50 |
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- | 0.6385 | 0.01 | 51 |
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- | 0.6426 | 0.01 | 52 |
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- | 0.6368 | 0.01 | 53 |
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- | 0.6285 | 0.01 | 54 |
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- | 0.6315 | 0.01 | 55 |
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- | 0.6246 | 0.01 | 56 |
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- | 0.6191 | 0.01 | 57 |
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- | 0.6242 | 0.01 | 58 |
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- | 0.6235 | 0.01 | 59 |
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- | 0.6205 | 0.01 | 60 |
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- | 0.6229 | 0.01 | 61 |
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- | 0.6108 | 0.01 | 62 |
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- | 0.6071 | 0.01 | 63 |
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- | 0.6030 | 0.01 | 64 |
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- | 0.6057 | 0.01 | 65 |
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- | 0.6052 | 0.01 | 66 |
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- | 0.6016 | 0.01 | 67 |
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- | 0.5998 | 0.01 | 68 |
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- | 0.5987 | 0.01 | 69 |
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- | 0.5992 | 0.01 | 70 |
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- | 0.5996 | 0.01 | 71 |
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- | 0.5941 | 0.01 | 72 |
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- | 0.5882 | 0.01 | 73 |
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- | 0.5949 | 0.01 | 74 |
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- | 0.5836 | 0.01 | 75 |
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- | 0.5891 | 0.01 | 76 |
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- | 0.5824 | 0.01 | 77 |
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- | 0.5845 | 0.01 | 78 |
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- | 0.5785 | 0.01 | 79 |
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- | 0.5775 | 0.01 | 80 |
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- | 0.5837 | 0.01 | 81 |
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- | 0.5836 | 0.01 | 82 |
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- | 0.5795 | 0.01 | 83 |
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- | 0.5801 | 0.01 | 84 |
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- | 0.5785 | 0.01 | 85 |
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- | 0.5778 | 0.01 | 86 |
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- | 0.5713 | 0.01 | 87 |
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- | 0.5703 | 0.01 | 88 |
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- | 0.5754 | 0.01 | 89 |
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- | 0.5681 | 0.01 | 90 |
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- | 0.5669 | 0.01 | 91 |
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- | 0.5663 | 0.01 | 92 |
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- | 0.5647 | 0.01 | 93 |
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- | 0.5684 | 0.01 | 94 |
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- | 0.5623 | 0.01 | 95 |
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- | 0.5622 | 0.01 | 96 |
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- | 0.5597 | 0.01 | 97 |
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- | 0.5592 | 0.01 | 98 |
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- | 0.5586 | 0.01 | 99 |
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- | 0.4859 | 0.0009999999 | 100 |
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- | 0.4874 | 0.0009999999 | 101 |
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- | 0.4794 | 0.0009999999 | 102 |
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- | 0.4802 | 0.0009999999 | 103 |
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- | 0.4763 | 0.0009999999 | 104 |
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- | 0.4776 | 0.0009999999 | 105 |
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- | 0.4758 | 0.0009999999 | 106 |
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- | 0.4751 | 0.0009999999 | 107 |
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- | 0.4785 | 0.0009999999 | 108 |
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- | 0.4766 | 0.0009999999 | 109 |
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- | 0.4741 | 0.0009999999 | 110 |
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- | 0.4739 | 0.0009999999 | 111 |
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- | 0.4756 | 0.0009999999 | 112 |
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- | 0.4697 | 0.0009999999 | 113 |
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- | 0.4733 | 0.0009999999 | 114 |
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- | 0.4746 | 0.0009999999 | 115 |
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- | 0.4733 | 0.0009999999 | 116 |
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- | 0.4749 | 0.0009999999 | 117 |
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- | 0.4767 | 0.0009999999 | 118 |
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- | 0.4721 | 0.0009999999 | 119 |
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- | 0.4697 | 0.0009999999 | 120 |
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- | 0.4709 | 0.0009999999 | 121 |
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- | 0.4709 | 0.0009999999 | 122 |
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- | 0.4699 | 0.0009999999 | 123 |
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- | 0.4731 | 0.0009999999 | 124 |
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- | 0.4708 | 0.0009999999 | 125 |
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- | 0.4728 | 0.0009999999 | 126 |
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- | 0.4678 | 0.0009999999 | 127 |
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- | 0.4699 | 0.0009999999 | 128 |
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- | 0.4706 | 0.0009999999 | 129 |
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- | 0.4703 | 0.0009999999 | 130 |
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- | 0.4691 | 0.0009999999 | 131 |
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- | 0.4701 | 0.0009999999 | 132 |
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- | 0.4680 | 0.0009999999 | 133 |
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- | 0.4666 | 0.0009999999 | 134 |
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- | 0.4701 | 0.0009999999 | 135 |
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- | 0.4690 | 0.0009999999 | 136 |
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- | 0.4703 | 0.0009999999 | 137 |
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- | 0.4712 | 0.0009999999 | 138 |
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- | 0.4753 | 0.0009999999 | 139 |
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- | 0.4694 | 0.0009999999 | 140 |
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- | 0.4702 | 0.0009999999 | 141 |
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- | 0.4653 | 0.0009999999 | 142 |
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- | 0.4687 | 0.0009999999 | 143 |
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- | 0.4706 | 0.0009999999 | 144 |
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- | 0.4649 | 0.0009999999 | 145 |
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- | 0.4659 | 0.0009999999 | 146 |
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- | 0.4685 | 0.0009999999 | 147 |
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- | 0.4702 | 0.0009999999 | 148 |
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- | 0.4674 | 0.0009999999 | 149 |
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- | 0.4623 | 9.999999e-05 | 150 |
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- | 0.4661 | 9.999999e-05 | 151 |
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- | 0.4614 | 9.999999e-05 | 152 |
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- | 0.4638 | 9.999999e-05 | 153 |
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- | 0.4625 | 9.999999e-05 | 154 |
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- | 0.4602 | 9.999999e-05 | 155 |
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- | 0.4661 | 9.999999e-05 | 156 |
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- | 0.4643 | 9.999999e-05 | 157 |
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- | 0.4629 | 9.999999e-05 | 158 |
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- | 0.4647 | 9.999999e-05 | 159 |
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- | 0.4642 | 9.999999e-05 | 160 |
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- | 0.4649 | 9.999999e-05 | 161 |
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- | 0.4609 | 9.999999e-05 | 162 |
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- | 0.4631 | 9.999999e-05 | 163 |
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- | 0.4663 | 9.999999e-05 | 164 |
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- | 0.4625 | 9.999999e-05 | 165 |
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- | 0.4616 | 9.999999e-05 | 166 |
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- | 0.4567 | 9.999999e-05 | 167 |
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- | 0.4567 | 9.999999e-05 | 168 |
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- | 0.4625 | 9.999999e-05 | 169 |
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- | 0.4639 | 9.999999e-05 | 170 |
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- | 0.4632 | 9.999999e-05 | 171 |
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- | 0.4606 | 9.999999e-05 | 172 |
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- | 0.4622 | 9.999999e-05 | 173 |
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- | 0.4621 | 9.999999e-05 | 174 |
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- | 0.4583 | 9.999999e-05 | 175 |
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- | 0.4586 | 9.999999e-05 | 176 |
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- | 0.4589 | 9.999999e-05 | 177 |
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- | 0.4568 | 9.999999e-05 | 178 |
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- | 0.4579 | 9.999999e-05 | 179 |
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- | 0.4634 | 9.999999e-05 | 180 |
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- | 0.4623 | 9.999999e-05 | 181 |
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- | 0.4645 | 9.999999e-05 | 182 |
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- | 0.4638 | 9.999999e-05 | 183 |
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- | 0.4610 | 9.999999e-05 | 184 |
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- | 0.4605 | 9.999999e-05 | 185 |
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- | 0.4636 | 9.999999e-05 | 186 |
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- | 0.4619 | 9.999999e-05 | 187 |
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- | 0.4627 | 9.999999e-05 | 188 |
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- | 0.4617 | 9.999999e-05 | 189 |
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- | 0.4607 | 9.999999e-05 | 190 |
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- | 0.4649 | 9.999999e-05 | 191 |
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- | 0.4601 | 9.999999e-05 | 192 |
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- | 0.4613 | 9.999999e-05 | 193 |
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- | 0.4608 | 9.999999e-05 | 194 |
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- | 0.4618 | 9.999999e-05 | 195 |
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- | 0.4593 | 9.999999e-05 | 196 |
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- | 0.4600 | 9.999999e-05 | 197 |
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- | 0.4580 | 9.999999e-05 | 198 |
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- | 0.4635 | 9.999999e-05 | 199 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [MJ199999/gpt3_model](https://huggingface.co/MJ199999/gpt3_model) on an unknown dataset.
15
  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.5845
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+ - Train Lr: 9.999999e-06
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+ - Epoch: 499
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20
  ## Model description
21
 
 
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  ### Training hyperparameters
35
 
36
  The following hyperparameters were used during training:
37
+ - optimizer: {'name': 'Adagrad', 'learning_rate': 9.999999e-06, 'decay': 0.0, 'initial_accumulator_value': 0.1, 'epsilon': 1e-07}
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  - training_precision: float32
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  ### Training results
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  | Train Loss | Train Lr | Epoch |
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  |:----------:|:------------:|:-----:|
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+ | 6.2880 | 0.01 | 0 |
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+ | 5.7606 | 0.01 | 1 |
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+ | 5.1576 | 0.01 | 2 |
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+ | 4.3108 | 0.01 | 3 |
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+ | 3.5814 | 0.01 | 4 |
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+ | 3.0632 | 0.01 | 5 |
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+ | 2.7176 | 0.01 | 6 |
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+ | 2.4443 | 0.01 | 7 |
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+ | 2.2514 | 0.01 | 8 |
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+ | 2.0976 | 0.01 | 9 |
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+ | 1.9442 | 0.01 | 10 |
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+ | 1.8267 | 0.01 | 11 |
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+ | 1.7501 | 0.01 | 12 |
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+ | 1.6662 | 0.01 | 13 |
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+ | 1.5683 | 0.01 | 14 |
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+ | 1.4911 | 0.01 | 15 |
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+ | 1.4178 | 0.01 | 16 |
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+ | 1.3575 | 0.01 | 17 |
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+ | 1.2840 | 0.01 | 18 |
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+ | 1.2293 | 0.01 | 19 |
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+ | 1.1635 | 0.01 | 20 |
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+ | 1.1338 | 0.01 | 21 |
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+ | 1.1031 | 0.01 | 22 |
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+ | 1.0701 | 0.01 | 23 |
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+ | 1.0398 | 0.01 | 24 |
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+ | 1.0211 | 0.01 | 25 |
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+ | 1.0005 | 0.01 | 26 |
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+ | 0.9744 | 0.01 | 27 |
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+ | 0.9637 | 0.01 | 28 |
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+ | 0.9429 | 0.01 | 29 |
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+ | 0.9272 | 0.01 | 30 |
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+ | 0.9216 | 0.01 | 31 |
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+ | 0.9131 | 0.01 | 32 |
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+ | 0.9008 | 0.01 | 33 |
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+ | 0.8897 | 0.01 | 34 |
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+ | 0.8916 | 0.01 | 35 |
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+ | 0.8700 | 0.01 | 36 |
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+ | 0.8633 | 0.01 | 37 |
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+ | 0.8630 | 0.01 | 38 |
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+ | 0.8583 | 0.01 | 39 |
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+ | 0.8512 | 0.01 | 40 |
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+ | 0.8424 | 0.01 | 41 |
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+ | 0.8403 | 0.01 | 42 |
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+ | 0.8285 | 0.01 | 43 |
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+ | 0.8285 | 0.01 | 44 |
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+ | 0.8238 | 0.01 | 45 |
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+ | 0.8100 | 0.01 | 46 |
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+ | 0.8149 | 0.01 | 47 |
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+ | 0.8067 | 0.01 | 48 |
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+ | 0.8109 | 0.01 | 49 |
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+ | 0.8055 | 0.01 | 50 |
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+ | 0.7995 | 0.01 | 51 |
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+ | 0.7915 | 0.01 | 52 |
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+ | 0.7938 | 0.01 | 53 |
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+ | 0.7876 | 0.01 | 54 |
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+ | 0.7864 | 0.01 | 55 |
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+ | 0.7795 | 0.01 | 56 |
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+ | 0.7841 | 0.01 | 57 |
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+ | 0.7803 | 0.01 | 58 |
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+ | 0.7713 | 0.01 | 59 |
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+ | 0.7694 | 0.01 | 60 |
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+ | 0.7726 | 0.01 | 61 |
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+ | 0.7648 | 0.01 | 62 |
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+ | 0.7661 | 0.01 | 63 |
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+ | 0.7584 | 0.01 | 64 |
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+ | 0.7646 | 0.01 | 65 |
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+ | 0.7544 | 0.01 | 66 |
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+ | 0.7532 | 0.01 | 67 |
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+ | 0.7516 | 0.01 | 68 |
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+ | 0.7482 | 0.01 | 69 |
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+ | 0.7489 | 0.01 | 70 |
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+ | 0.7455 | 0.01 | 71 |
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+ | 0.7456 | 0.01 | 72 |
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+ | 0.7486 | 0.01 | 73 |
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+ | 0.7413 | 0.01 | 74 |
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+ | 0.7467 | 0.01 | 75 |
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+ | 0.7406 | 0.01 | 76 |
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+ | 0.7387 | 0.01 | 77 |
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+ | 0.7367 | 0.01 | 78 |
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+ | 0.7378 | 0.01 | 79 |
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+ | 0.7330 | 0.01 | 80 |
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+ | 0.7299 | 0.01 | 81 |
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+ | 0.7290 | 0.01 | 82 |
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+ | 0.7293 | 0.01 | 83 |
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+ | 0.7226 | 0.01 | 84 |
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+ | 0.7222 | 0.01 | 85 |
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+ | 0.7186 | 0.01 | 86 |
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+ | 0.7244 | 0.01 | 87 |
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+ | 0.7205 | 0.01 | 88 |
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+ | 0.7207 | 0.01 | 89 |
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+ | 0.7211 | 0.01 | 90 |
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+ | 0.7225 | 0.01 | 91 |
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+ | 0.7147 | 0.01 | 92 |
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+ | 0.7131 | 0.01 | 93 |
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+ | 0.7083 | 0.01 | 94 |
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+ | 0.7110 | 0.01 | 95 |
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+ | 0.7114 | 0.01 | 96 |
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+ | 0.7141 | 0.01 | 97 |
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+ | 0.7108 | 0.01 | 98 |
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+ | 0.7126 | 0.01 | 99 |
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+ | 0.7075 | 0.01 | 100 |
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+ | 0.7071 | 0.01 | 101 |
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+ | 0.6950 | 0.01 | 102 |
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+ | 0.7033 | 0.01 | 103 |
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+ | 0.6956 | 0.01 | 104 |
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+ | 0.7001 | 0.01 | 105 |
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+ | 0.6964 | 0.01 | 106 |
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+ | 0.6935 | 0.01 | 107 |
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+ | 0.6916 | 0.01 | 108 |
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+ | 0.7012 | 0.01 | 109 |
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+ | 0.6924 | 0.01 | 110 |
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+ | 0.6933 | 0.01 | 111 |
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+ | 0.6919 | 0.01 | 112 |
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+ | 0.6920 | 0.01 | 113 |
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+ | 0.6923 | 0.01 | 114 |
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+ | 0.6824 | 0.01 | 115 |
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+ | 0.6885 | 0.01 | 116 |
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+ | 0.6905 | 0.01 | 117 |
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+ | 0.6862 | 0.01 | 118 |
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+ | 0.6857 | 0.01 | 119 |
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+ | 0.6827 | 0.01 | 120 |
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+ | 0.6880 | 0.01 | 121 |
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+ | 0.6816 | 0.01 | 122 |
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+ | 0.6843 | 0.01 | 123 |
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+ | 0.6751 | 0.01 | 124 |
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+ | 0.6836 | 0.01 | 125 |
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+ | 0.6762 | 0.01 | 126 |
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+ | 0.6797 | 0.01 | 127 |
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+ | 0.6840 | 0.01 | 128 |
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+ | 0.6793 | 0.01 | 129 |
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+ | 0.6745 | 0.01 | 130 |
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+ | 0.6804 | 0.01 | 131 |
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+ | 0.6762 | 0.01 | 132 |
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+ | 0.6777 | 0.01 | 133 |
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+ | 0.6709 | 0.01 | 134 |
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+ | 0.6759 | 0.01 | 135 |
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+ | 0.6739 | 0.01 | 136 |
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+ | 0.6772 | 0.01 | 137 |
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+ | 0.6720 | 0.01 | 138 |
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+ | 0.6757 | 0.01 | 139 |
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+ | 0.6623 | 0.01 | 140 |
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+ | 0.6710 | 0.01 | 141 |
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+ | 0.6704 | 0.01 | 142 |
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+ | 0.6673 | 0.01 | 143 |
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+ | 0.6684 | 0.01 | 144 |
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+ | 0.6700 | 0.01 | 145 |
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+ | 0.6681 | 0.01 | 146 |
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+ | 0.6685 | 0.01 | 147 |
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+ | 0.6688 | 0.01 | 148 |
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+ | 0.6602 | 0.01 | 149 |
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+ | 0.6611 | 0.01 | 150 |
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+ | 0.6651 | 0.01 | 151 |
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+ | 0.6656 | 0.01 | 152 |
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+ | 0.6639 | 0.01 | 153 |
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+ | 0.6596 | 0.01 | 154 |
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+ | 0.6707 | 0.01 | 155 |
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+ | 0.6702 | 0.01 | 156 |
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+ | 0.6616 | 0.01 | 157 |
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+ | 0.6675 | 0.01 | 158 |
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+ | 0.6574 | 0.01 | 159 |
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+ | 0.6606 | 0.01 | 160 |
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+ | 0.6550 | 0.01 | 161 |
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+ | 0.6605 | 0.01 | 162 |
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+ | 0.6612 | 0.01 | 163 |
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+ | 0.6597 | 0.01 | 164 |
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+ | 0.6566 | 0.01 | 165 |
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+ | 0.6579 | 0.01 | 166 |
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+ | 0.6535 | 0.01 | 167 |
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+ | 0.6550 | 0.01 | 168 |
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+ | 0.6531 | 0.01 | 169 |
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+ | 0.6579 | 0.01 | 170 |
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+ | 0.6592 | 0.01 | 171 |
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+ | 0.6597 | 0.01 | 172 |
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+ | 0.6556 | 0.01 | 173 |
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+ | 0.6558 | 0.01 | 174 |
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+ | 0.6529 | 0.01 | 175 |
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221
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546
  ### Framework versions
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