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--- |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: gpt3_model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# gpt3_model |
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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: 0.4905 |
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- Train Lr: 0.0009999999 |
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- Epoch: 199 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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': 0.0009999999, '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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| 5.1583 | 0.01 | 0 | |
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| 3.9477 | 0.01 | 1 | |
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| 2.9332 | 0.01 | 2 | |
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| 2.1581 | 0.01 | 3 | |
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| 1.6918 | 0.01 | 4 | |
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| 1.3929 | 0.01 | 5 | |
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| 1.2062 | 0.01 | 6 | |
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| 1.0955 | 0.01 | 7 | |
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| 1.0068 | 0.01 | 8 | |
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| 0.9528 | 0.01 | 9 | |
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| 0.9051 | 0.01 | 10 | |
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| 0.8710 | 0.01 | 11 | |
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| 0.8564 | 0.01 | 12 | |
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| 0.8094 | 0.01 | 13 | |
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| 0.8143 | 0.01 | 14 | |
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| 0.7853 | 0.01 | 15 | |
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| 0.7625 | 0.01 | 16 | |
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| 0.7508 | 0.01 | 17 | |
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| 0.7449 | 0.01 | 18 | |
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| 0.7319 | 0.01 | 19 | |
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| 0.7144 | 0.01 | 20 | |
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| 0.7045 | 0.01 | 21 | |
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| 0.7029 | 0.01 | 22 | |
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| 0.6937 | 0.01 | 23 | |
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| 0.6898 | 0.01 | 24 | |
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| 0.6745 | 0.01 | 25 | |
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| 0.6767 | 0.01 | 26 | |
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| 0.6692 | 0.01 | 27 | |
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| 0.6604 | 0.01 | 28 | |
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| 0.6573 | 0.01 | 29 | |
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| 0.6524 | 0.01 | 30 | |
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| 0.6508 | 0.01 | 31 | |
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| 0.6443 | 0.01 | 32 | |
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| 0.6452 | 0.01 | 33 | |
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| 0.6371 | 0.01 | 34 | |
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| 0.6362 | 0.01 | 35 | |
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| 0.6304 | 0.01 | 36 | |
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| 0.6317 | 0.01 | 37 | |
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| 0.6270 | 0.01 | 38 | |
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| 0.6257 | 0.01 | 39 | |
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| 0.6208 | 0.01 | 40 | |
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| 0.6227 | 0.01 | 41 | |
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| 0.6154 | 0.01 | 42 | |
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| 0.6126 | 0.01 | 43 | |
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| 0.6149 | 0.01 | 44 | |
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| 0.6075 | 0.01 | 45 | |
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| 0.6084 | 0.01 | 46 | |
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| 0.6078 | 0.01 | 47 | |
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| 0.6057 | 0.01 | 48 | |
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| 0.6033 | 0.01 | 49 | |
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| 0.6040 | 0.01 | 50 | |
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| 0.5989 | 0.01 | 51 | |
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| 0.5967 | 0.01 | 52 | |
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| 0.5952 | 0.01 | 53 | |
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| 0.5911 | 0.01 | 54 | |
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| 0.5904 | 0.01 | 55 | |
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| 0.5888 | 0.01 | 56 | |
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| 0.5886 | 0.01 | 57 | |
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| 0.5883 | 0.01 | 58 | |
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| 0.5838 | 0.01 | 59 | |
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| 0.5856 | 0.01 | 60 | |
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| 0.5850 | 0.01 | 61 | |
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| 0.5801 | 0.01 | 62 | |
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| 0.5821 | 0.01 | 63 | |
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| 0.5781 | 0.01 | 64 | |
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| 0.5786 | 0.01 | 65 | |
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| 0.5835 | 0.01 | 66 | |
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| 0.5808 | 0.01 | 67 | |
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| 0.5754 | 0.01 | 68 | |
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| 0.5742 | 0.01 | 69 | |
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| 0.5733 | 0.01 | 70 | |
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| 0.5700 | 0.01 | 71 | |
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| 0.5738 | 0.01 | 72 | |
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| 0.5678 | 0.01 | 73 | |
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| 0.5695 | 0.01 | 74 | |
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| 0.5684 | 0.01 | 75 | |
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| 0.5696 | 0.01 | 76 | |
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| 0.5688 | 0.01 | 77 | |
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| 0.5648 | 0.01 | 78 | |
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| 0.5592 | 0.01 | 79 | |
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| 0.5622 | 0.01 | 80 | |
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| 0.5660 | 0.01 | 81 | |
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| 0.5636 | 0.01 | 82 | |
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| 0.5602 | 0.01 | 83 | |
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| 0.5613 | 0.01 | 84 | |
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| 0.5608 | 0.01 | 85 | |
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| 0.5589 | 0.01 | 86 | |
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| 0.5580 | 0.01 | 87 | |
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| 0.5566 | 0.01 | 88 | |
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| 0.5531 | 0.01 | 89 | |
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| 0.5571 | 0.01 | 90 | |
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| 0.5541 | 0.01 | 91 | |
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| 0.5576 | 0.01 | 92 | |
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| 0.5560 | 0.01 | 93 | |
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| 0.5517 | 0.01 | 94 | |
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| 0.5508 | 0.01 | 95 | |
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| 0.5554 | 0.01 | 96 | |
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| 0.5539 | 0.01 | 97 | |
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| 0.5493 | 0.01 | 98 | |
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| 0.5499 | 0.01 | 99 | |
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| 0.4999 | 0.0009999999 | 100 | |
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| 0.4981 | 0.0009999999 | 101 | |
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| 0.4983 | 0.0009999999 | 102 | |
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| 0.4984 | 0.0009999999 | 103 | |
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| 0.4974 | 0.0009999999 | 104 | |
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| 0.4957 | 0.0009999999 | 105 | |
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| 0.4966 | 0.0009999999 | 106 | |
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| 0.4975 | 0.0009999999 | 107 | |
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| 0.4962 | 0.0009999999 | 108 | |
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| 0.4932 | 0.0009999999 | 109 | |
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| 0.4983 | 0.0009999999 | 110 | |
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| 0.4937 | 0.0009999999 | 111 | |
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| 0.4926 | 0.0009999999 | 112 | |
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| 0.4944 | 0.0009999999 | 113 | |
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| 0.4947 | 0.0009999999 | 114 | |
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| 0.4953 | 0.0009999999 | 115 | |
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| 0.4934 | 0.0009999999 | 116 | |
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| 0.4929 | 0.0009999999 | 117 | |
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| 0.4925 | 0.0009999999 | 118 | |
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| 0.4948 | 0.0009999999 | 119 | |
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| 0.4947 | 0.0009999999 | 120 | |
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| 0.4936 | 0.0009999999 | 121 | |
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| 0.4909 | 0.0009999999 | 122 | |
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| 0.4960 | 0.0009999999 | 123 | |
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| 0.4952 | 0.0009999999 | 124 | |
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| 0.4923 | 0.0009999999 | 125 | |
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| 0.4930 | 0.0009999999 | 126 | |
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| 0.4942 | 0.0009999999 | 127 | |
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| 0.4927 | 0.0009999999 | 128 | |
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| 0.4917 | 0.0009999999 | 129 | |
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| 0.4926 | 0.0009999999 | 130 | |
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| 0.4927 | 0.0009999999 | 131 | |
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| 0.4932 | 0.0009999999 | 132 | |
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| 0.4925 | 0.0009999999 | 133 | |
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| 0.4928 | 0.0009999999 | 134 | |
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| 0.4936 | 0.0009999999 | 135 | |
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| 0.4908 | 0.0009999999 | 136 | |
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| 0.4936 | 0.0009999999 | 137 | |
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| 0.4916 | 0.0009999999 | 138 | |
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| 0.4906 | 0.0009999999 | 139 | |
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| 0.4904 | 0.0009999999 | 140 | |
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| 0.4920 | 0.0009999999 | 141 | |
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| 0.4924 | 0.0009999999 | 142 | |
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| 0.4902 | 0.0009999999 | 143 | |
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| 0.4903 | 0.0009999999 | 144 | |
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| 0.4903 | 0.0009999999 | 145 | |
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| 0.4924 | 0.0009999999 | 146 | |
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| 0.4889 | 0.0009999999 | 147 | |
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| 0.4896 | 0.0009999999 | 148 | |
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| 0.4919 | 0.0009999999 | 149 | |
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| 0.4896 | 0.0009999999 | 150 | |
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| 0.4906 | 0.0009999999 | 151 | |
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| 0.4923 | 0.0009999999 | 152 | |
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| 0.4899 | 0.0009999999 | 153 | |
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| 0.4925 | 0.0009999999 | 154 | |
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| 0.4901 | 0.0009999999 | 155 | |
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| 0.4910 | 0.0009999999 | 156 | |
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| 0.4904 | 0.0009999999 | 157 | |
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| 0.4912 | 0.0009999999 | 158 | |
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| 0.4937 | 0.0009999999 | 159 | |
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| 0.4894 | 0.0009999999 | 160 | |
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| 0.4913 | 0.0009999999 | 161 | |
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| 0.4899 | 0.0009999999 | 162 | |
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| 0.4894 | 0.0009999999 | 163 | |
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| 0.4904 | 0.0009999999 | 164 | |
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| 0.4900 | 0.0009999999 | 165 | |
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| 0.4890 | 0.0009999999 | 166 | |
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| 0.4919 | 0.0009999999 | 167 | |
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| 0.4909 | 0.0009999999 | 168 | |
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| 0.4891 | 0.0009999999 | 169 | |
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| 0.4900 | 0.0009999999 | 170 | |
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| 0.4910 | 0.0009999999 | 171 | |
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| 0.4901 | 0.0009999999 | 172 | |
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| 0.4914 | 0.0009999999 | 173 | |
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| 0.4913 | 0.0009999999 | 174 | |
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| 0.4897 | 0.0009999999 | 175 | |
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| 0.4892 | 0.0009999999 | 176 | |
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| 0.4929 | 0.0009999999 | 177 | |
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| 0.4881 | 0.0009999999 | 178 | |
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| 0.4920 | 0.0009999999 | 179 | |
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| 0.4888 | 0.0009999999 | 180 | |
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| 0.4901 | 0.0009999999 | 181 | |
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| 0.4875 | 0.0009999999 | 182 | |
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| 0.4930 | 0.0009999999 | 183 | |
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| 0.4867 | 0.0009999999 | 184 | |
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| 0.4890 | 0.0009999999 | 185 | |
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| 0.4898 | 0.0009999999 | 186 | |
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| 0.4880 | 0.0009999999 | 187 | |
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| 0.4899 | 0.0009999999 | 188 | |
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| 0.4881 | 0.0009999999 | 189 | |
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| 0.4897 | 0.0009999999 | 190 | |
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| 0.4876 | 0.0009999999 | 191 | |
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| 0.4873 | 0.0009999999 | 192 | |
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| 0.4901 | 0.0009999999 | 193 | |
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| 0.4898 | 0.0009999999 | 194 | |
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| 0.4898 | 0.0009999999 | 195 | |
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| 0.4861 | 0.0009999999 | 196 | |
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| 0.4878 | 0.0009999999 | 197 | |
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| 0.4880 | 0.0009999999 | 198 | |
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| 0.4905 | 0.0009999999 | 199 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- TensorFlow 2.8.2 |
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- Tokenizers 0.12.1 |
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