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--- |
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base_model: Malvegil/prologue_creator-model |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Malvegil/prologue_creator-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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# Malvegil/prologue_creator-model |
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This model is a fine-tuned version of [Malvegil/prologue_creator-model](https://huggingface.co/Malvegil/prologue_creator-model) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.8078 |
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- Validation Loss: 5.6164 |
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- Epoch: 235 |
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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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 9.6983 | 8.6325 | 0 | |
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| 7.5394 | 7.4380 | 1 | |
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| 6.8454 | 6.9855 | 2 | |
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| 6.5034 | 6.8347 | 3 | |
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| 6.3289 | 6.6883 | 4 | |
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| 6.1540 | 6.5173 | 5 | |
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| 6.0244 | 6.3997 | 6 | |
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| 5.9258 | 6.3245 | 7 | |
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| 5.8095 | 6.2648 | 8 | |
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| 5.7688 | 6.1865 | 9 | |
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| 5.6244 | 6.1095 | 10 | |
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| 5.5619 | 6.0552 | 11 | |
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| 5.4940 | 6.0000 | 12 | |
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| 5.3603 | 5.9456 | 13 | |
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| 5.2852 | 5.8861 | 14 | |
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| 5.2218 | 5.8256 | 15 | |
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| 5.1715 | 5.7722 | 16 | |
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| 5.0556 | 5.7236 | 17 | |
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| 5.0339 | 5.6669 | 18 | |
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| 4.8776 | 5.6155 | 19 | |
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| 4.9133 | 5.5683 | 20 | |
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| 4.8350 | 5.5166 | 21 | |
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| 4.6951 | 5.4712 | 22 | |
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| 4.7144 | 5.4447 | 23 | |
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| 4.6560 | 5.3954 | 24 | |
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| 4.6125 | 5.3449 | 25 | |
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| 4.5494 | 5.3382 | 26 | |
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| 4.3536 | 5.2989 | 27 | |
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| 4.3613 | 5.2537 | 28 | |
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| 4.3123 | 5.2269 | 29 | |
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| 4.2677 | 5.2115 | 30 | |
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| 4.2407 | 5.1566 | 31 | |
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| 4.1543 | 5.1413 | 32 | |
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| 4.0961 | 5.1284 | 33 | |
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| 4.0779 | 5.0771 | 34 | |
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| 4.0303 | 5.0722 | 35 | |
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| 3.9734 | 5.0550 | 36 | |
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| 3.9541 | 5.0060 | 37 | |
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| 3.9188 | 4.9941 | 38 | |
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| 3.8350 | 4.9851 | 39 | |
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| 3.8081 | 4.9648 | 40 | |
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| 3.7395 | 4.9533 | 41 | |
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| 3.7045 | 4.9112 | 42 | |
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| 3.6765 | 4.9185 | 43 | |
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| 3.5667 | 4.8981 | 44 | |
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| 3.5491 | 4.8510 | 45 | |
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| 3.5547 | 4.8688 | 46 | |
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| 3.5317 | 4.8393 | 47 | |
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| 3.4210 | 4.8366 | 48 | |
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| 3.4503 | 4.8120 | 49 | |
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| 3.4187 | 4.8045 | 50 | |
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| 3.3313 | 4.7899 | 51 | |
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| 3.2695 | 4.7733 | 52 | |
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| 3.2980 | 4.7643 | 53 | |
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| 3.2614 | 4.7592 | 54 | |
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| 3.2011 | 4.7353 | 55 | |
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| 3.1756 | 4.7323 | 56 | |
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| 3.1325 | 4.7405 | 57 | |
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| 3.1642 | 4.6849 | 58 | |
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| 3.0915 | 4.7039 | 59 | |
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| 3.0950 | 4.6905 | 60 | |
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| 2.9946 | 4.6777 | 61 | |
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| 3.0338 | 4.7064 | 62 | |
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| 2.9554 | 4.6617 | 63 | |
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| 2.9999 | 4.6723 | 64 | |
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| 2.9410 | 4.6397 | 65 | |
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| 2.9157 | 4.6493 | 66 | |
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| 2.8930 | 4.6641 | 67 | |
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| 2.8620 | 4.6019 | 68 | |
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| 2.8726 | 4.6564 | 69 | |
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| 2.8386 | 4.6286 | 70 | |
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| 2.8574 | 4.6259 | 71 | |
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| 2.8023 | 4.6359 | 72 | |
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| 2.7938 | 4.6031 | 73 | |
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| 2.7686 | 4.6159 | 74 | |
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| 2.7211 | 4.6128 | 75 | |
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| 2.6670 | 4.5913 | 76 | |
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| 2.6814 | 4.6226 | 77 | |
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| 2.6588 | 4.6188 | 78 | |
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| 2.6030 | 4.5964 | 79 | |
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| 2.6216 | 4.6019 | 80 | |
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| 2.5280 | 4.6018 | 81 | |
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| 2.5754 | 4.5851 | 82 | |
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| 2.5673 | 4.5901 | 83 | |
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| 2.5393 | 4.6256 | 84 | |
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| 2.4955 | 4.5802 | 85 | |
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| 2.4958 | 4.6054 | 86 | |
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| 2.5005 | 4.6039 | 87 | |
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| 2.4841 | 4.5920 | 88 | |
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| 2.4570 | 4.6012 | 89 | |
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| 2.4515 | 4.5890 | 90 | |
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| 2.4431 | 4.5838 | 91 | |
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| 2.3742 | 4.5787 | 92 | |
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| 2.3844 | 4.6137 | 93 | |
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| 2.3383 | 4.5567 | 94 | |
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| 2.3353 | 4.6001 | 95 | |
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| 2.3191 | 4.5930 | 96 | |
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| 2.3239 | 4.6078 | 97 | |
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| 2.2769 | 4.6426 | 98 | |
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| 2.3320 | 4.5895 | 99 | |
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| 2.2817 | 4.5816 | 100 | |
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| 2.2582 | 4.6319 | 101 | |
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| 2.1774 | 4.6308 | 102 | |
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| 2.2102 | 4.6072 | 103 | |
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| 2.1617 | 4.6217 | 104 | |
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| 2.1204 | 4.6111 | 105 | |
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| 2.1133 | 4.6397 | 106 | |
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| 2.1467 | 4.6421 | 107 | |
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| 2.1342 | 4.6318 | 108 | |
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| 2.1181 | 4.6555 | 109 | |
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| 2.0767 | 4.6562 | 110 | |
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| 2.0712 | 4.6533 | 111 | |
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| 2.0510 | 4.6722 | 112 | |
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| 2.0286 | 4.6437 | 113 | |
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| 2.0246 | 4.6431 | 114 | |
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| 2.0103 | 4.6450 | 115 | |
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| 2.0312 | 4.7080 | 116 | |
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| 2.0114 | 4.6146 | 117 | |
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| 1.9577 | 4.7103 | 118 | |
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| 1.9565 | 4.6865 | 119 | |
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| 1.9472 | 4.6602 | 120 | |
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| 1.9208 | 4.7423 | 121 | |
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| 1.8886 | 4.6638 | 122 | |
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| 1.9209 | 4.7388 | 123 | |
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| 1.8418 | 4.6900 | 124 | |
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| 1.8558 | 4.7059 | 125 | |
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| 1.8710 | 4.7353 | 126 | |
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| 1.8964 | 4.6955 | 127 | |
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| 1.8434 | 4.7402 | 128 | |
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| 1.8208 | 4.7557 | 129 | |
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| 1.8239 | 4.7254 | 130 | |
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| 1.8503 | 4.7575 | 131 | |
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| 1.7790 | 4.7725 | 132 | |
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| 1.7704 | 4.7971 | 133 | |
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| 1.7516 | 4.7445 | 134 | |
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| 1.7630 | 4.8046 | 135 | |
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| 1.7549 | 4.8150 | 136 | |
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| 1.7104 | 4.7884 | 137 | |
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| 1.6935 | 4.8472 | 138 | |
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| 1.6870 | 4.8170 | 139 | |
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| 1.6855 | 4.7915 | 140 | |
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| 1.6557 | 4.8719 | 141 | |
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| 1.6574 | 4.8336 | 142 | |
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| 1.5848 | 4.8889 | 143 | |
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| 1.6420 | 4.8585 | 144 | |
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| 1.6126 | 4.8700 | 145 | |
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| 1.5733 | 4.8807 | 146 | |
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| 1.5987 | 4.9093 | 147 | |
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| 1.5042 | 4.8983 | 148 | |
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| 1.5607 | 4.9012 | 149 | |
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| 1.5851 | 4.9208 | 150 | |
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| 1.5446 | 4.9047 | 151 | |
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| 1.5388 | 4.9215 | 152 | |
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| 1.5056 | 4.9796 | 153 | |
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| 1.5179 | 4.9090 | 154 | |
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| 1.4876 | 4.9935 | 155 | |
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| 1.4975 | 4.9810 | 156 | |
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| 1.4607 | 5.0071 | 157 | |
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| 1.5030 | 4.9251 | 158 | |
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| 1.4315 | 5.0219 | 159 | |
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| 1.4314 | 4.9997 | 160 | |
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| 1.4178 | 4.9675 | 161 | |
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| 1.4635 | 5.0669 | 162 | |
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| 1.4097 | 5.0152 | 163 | |
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| 1.4132 | 5.0367 | 164 | |
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| 1.3775 | 5.0395 | 165 | |
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| 1.4041 | 5.0492 | 166 | |
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| 1.3943 | 5.0470 | 167 | |
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| 1.3495 | 5.1050 | 168 | |
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| 1.3552 | 5.1041 | 169 | |
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| 1.3615 | 5.0648 | 170 | |
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| 1.3254 | 5.1234 | 171 | |
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| 1.3445 | 5.0723 | 172 | |
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| 1.3316 | 5.1059 | 173 | |
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| 1.3324 | 5.1294 | 174 | |
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| 1.2835 | 5.1263 | 175 | |
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| 1.2682 | 5.1415 | 176 | |
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| 1.2784 | 5.0970 | 177 | |
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| 1.2765 | 5.1549 | 178 | |
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| 1.2319 | 5.1690 | 179 | |
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| 1.2499 | 5.1262 | 180 | |
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| 1.1930 | 5.2097 | 181 | |
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| 1.1929 | 5.1751 | 182 | |
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| 1.2155 | 5.1879 | 183 | |
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| 1.1793 | 5.2163 | 184 | |
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| 1.2233 | 5.2055 | 185 | |
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| 1.1913 | 5.2115 | 186 | |
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| 1.1525 | 5.2521 | 187 | |
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| 1.1655 | 5.2302 | 188 | |
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| 1.1481 | 5.2551 | 189 | |
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| 1.1580 | 5.2635 | 190 | |
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| 1.1389 | 5.2528 | 191 | |
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| 1.1284 | 5.2694 | 192 | |
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| 1.1326 | 5.2906 | 193 | |
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| 1.1092 | 5.2957 | 194 | |
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| 1.0763 | 5.3227 | 195 | |
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| 1.0933 | 5.3446 | 196 | |
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| 1.0921 | 5.3191 | 197 | |
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| 1.0771 | 5.3399 | 198 | |
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| 1.0682 | 5.3906 | 199 | |
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| 1.0679 | 5.3286 | 200 | |
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| 1.0526 | 5.3256 | 201 | |
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| 1.0728 | 5.3739 | 202 | |
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| 1.0440 | 5.3422 | 203 | |
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| 1.0250 | 5.3946 | 204 | |
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| 1.0444 | 5.3930 | 205 | |
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| 1.0013 | 5.4044 | 206 | |
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| 0.9885 | 5.4122 | 207 | |
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| 1.0002 | 5.4359 | 208 | |
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| 0.9855 | 5.4380 | 209 | |
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| 0.9918 | 5.4045 | 210 | |
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| 0.9711 | 5.4300 | 211 | |
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| 0.9513 | 5.4863 | 212 | |
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| 0.9615 | 5.4596 | 213 | |
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| 0.9264 | 5.4859 | 214 | |
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| 0.9255 | 5.4913 | 215 | |
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| 0.9387 | 5.4630 | 216 | |
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| 0.9216 | 5.4758 | 217 | |
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| 0.9157 | 5.4729 | 218 | |
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| 0.8907 | 5.5127 | 219 | |
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| 0.9049 | 5.5270 | 220 | |
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| 0.8869 | 5.5087 | 221 | |
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| 0.8787 | 5.5236 | 222 | |
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| 0.8839 | 5.5024 | 223 | |
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| 0.8711 | 5.5289 | 224 | |
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| 0.8663 | 5.5205 | 225 | |
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| 0.8504 | 5.5972 | 226 | |
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| 0.8532 | 5.5749 | 227 | |
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| 0.8397 | 5.5873 | 228 | |
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| 0.8358 | 5.5819 | 229 | |
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| 0.8230 | 5.5610 | 230 | |
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| 0.8384 | 5.5884 | 231 | |
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| 0.8251 | 5.5783 | 232 | |
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| 0.8137 | 5.5916 | 233 | |
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| 0.8078 | 5.6334 | 234 | |
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| 0.8078 | 5.6164 | 235 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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