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@@ -1,21 +1,20 @@
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  ---
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- license: mit
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- base_model: roberta-base
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: roberta-2020-Q1-filtered
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  results: []
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  ---
10
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # roberta-2020-Q1-filtered
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- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.7087
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  ## Model description
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@@ -47,306 +46,306 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-------:|:---------------:|
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- | No log | 0.07 | 8000 | 2.9780 |
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- | 3.1296 | 0.13 | 16000 | 2.8948 |
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- | 3.1296 | 0.2 | 24000 | 2.8590 |
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- | 2.9018 | 0.26 | 32000 | 2.8033 |
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- | 2.9018 | 0.33 | 40000 | 2.7938 |
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- | 2.8331 | 0.39 | 48000 | 2.7695 |
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- | 2.8331 | 0.46 | 56000 | 2.7614 |
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- | 2.7723 | 0.52 | 64000 | 2.7417 |
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- | 2.7723 | 0.59 | 72000 | 2.7249 |
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- | 2.75 | 0.65 | 80000 | 2.7202 |
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- | 2.75 | 0.72 | 88000 | 2.7112 |
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- | 2.735 | 0.78 | 96000 | 2.7229 |
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- | 2.735 | 0.85 | 104000 | 2.7371 |
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- | 2.7137 | 0.91 | 112000 | 2.7059 |
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- | 2.7137 | 0.98 | 120000 | 2.7121 |
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- | 2.7155 | 1.04 | 128000 | 2.7249 |
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- | 2.7155 | 1.11 | 136000 | 2.7131 |
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- | 2.7152 | 1.17 | 144000 | 2.7000 |
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- | 2.7152 | 1.24 | 152000 | 2.7030 |
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- | 2.7151 | 1.3 | 160000 | 2.7214 |
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- | 2.7151 | 1.37 | 168000 | 2.7076 |
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- | 2.7166 | 1.44 | 176000 | 2.7106 |
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- | 2.7166 | 1.5 | 184000 | 2.7197 |
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- | 2.7144 | 1.57 | 192000 | 2.7101 |
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- | 2.7144 | 1.63 | 200000 | 2.7235 |
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- | 2.7179 | 1.7 | 208000 | 2.7066 |
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- | 2.7179 | 1.76 | 216000 | 2.7283 |
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- | 2.7231 | 1.83 | 224000 | 2.7203 |
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- | 2.7231 | 1.89 | 232000 | 2.7111 |
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- | 2.7284 | 1.96 | 240000 | 2.7217 |
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- | 2.7284 | 2.02 | 248000 | 2.7251 |
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- | 2.7242 | 2.09 | 256000 | 2.7181 |
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- | 2.7242 | 2.15 | 264000 | 2.7238 |
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- | 2.7171 | 2.22 | 272000 | 2.7488 |
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- | 2.7171 | 2.28 | 280000 | 2.7315 |
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- | 2.7312 | 2.35 | 288000 | 2.7469 |
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- | 2.7312 | 2.41 | 296000 | 2.7363 |
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- | 2.7386 | 2.48 | 304000 | 2.7398 |
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- | 2.7386 | 2.54 | 312000 | 2.7477 |
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- | 2.7457 | 2.61 | 320000 | 2.7536 |
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- | 2.7457 | 2.67 | 328000 | 2.7483 |
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- | 2.7496 | 2.74 | 336000 | 2.7529 |
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- | 2.7496 | 2.8 | 344000 | 2.7492 |
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- | 2.7521 | 2.87 | 352000 | 2.7612 |
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- | 2.7521 | 2.94 | 360000 | 2.7701 |
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- | 2.7649 | 3.0 | 368000 | 2.7705 |
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- | 2.7649 | 3.07 | 376000 | 2.7828 |
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- | 2.7516 | 3.13 | 384000 | 2.7680 |
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- | 2.7516 | 3.2 | 392000 | 2.7843 |
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- | 2.762 | 3.26 | 400000 | 2.7916 |
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- | 2.762 | 3.33 | 408000 | 2.7692 |
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- | 2.7789 | 3.39 | 416000 | 2.7834 |
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- | 2.7789 | 3.46 | 424000 | 2.7788 |
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- | 2.7879 | 3.52 | 432000 | 2.8037 |
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- | 2.7879 | 3.59 | 440000 | 2.7919 |
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- | 2.7853 | 3.65 | 448000 | 2.8077 |
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- | 2.7853 | 3.72 | 456000 | 2.7903 |
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- | 2.7976 | 3.78 | 464000 | 2.8109 |
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- | 2.7976 | 3.85 | 472000 | 2.7957 |
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- | 2.789 | 3.91 | 480000 | 2.8023 |
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- | 2.789 | 3.98 | 488000 | 2.8126 |
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- | 2.8089 | 4.04 | 496000 | 2.8154 |
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- | 2.8089 | 4.11 | 504000 | 2.8123 |
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- | 2.7915 | 4.17 | 512000 | 2.8146 |
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- | 2.7915 | 4.24 | 520000 | 2.8250 |
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- | 2.8094 | 4.31 | 528000 | 2.8206 |
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- | 2.8094 | 4.37 | 536000 | 2.8182 |
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- | 2.8196 | 4.44 | 544000 | 2.8351 |
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- | 2.8196 | 4.5 | 552000 | 2.8394 |
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- | 2.8316 | 4.57 | 560000 | 2.8397 |
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- | 2.8316 | 4.63 | 568000 | 2.8403 |
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- | 2.8444 | 4.7 | 576000 | 2.8351 |
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- | 2.8444 | 4.76 | 584000 | 2.8574 |
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- | 2.833 | 4.83 | 592000 | 2.8617 |
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- | 2.833 | 4.89 | 600000 | 2.8578 |
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- | 2.839 | 4.96 | 608000 | 2.8577 |
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- | 2.839 | 5.02 | 616000 | 2.8727 |
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- | 2.8427 | 5.09 | 624000 | 2.8586 |
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- | 2.8427 | 5.15 | 632000 | 2.8808 |
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- | 2.8599 | 5.22 | 640000 | 2.8960 |
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- | 2.8599 | 5.28 | 648000 | 2.8883 |
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- | 2.8694 | 5.35 | 656000 | 2.8885 |
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- | 2.8694 | 5.41 | 664000 | 2.8873 |
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- | 2.8626 | 5.48 | 672000 | 2.8930 |
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- | 2.8626 | 5.54 | 680000 | 2.8988 |
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- | 2.8921 | 5.61 | 688000 | 2.9117 |
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- | 2.8921 | 5.68 | 696000 | 2.9122 |
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- | 2.8884 | 5.74 | 704000 | 2.9001 |
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- | 2.8884 | 5.81 | 712000 | 2.9094 |
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- | 2.8974 | 5.87 | 720000 | 2.9110 |
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- | 2.8974 | 5.94 | 728000 | 2.9045 |
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- | 2.903 | 6.0 | 736000 | 2.9337 |
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- | 2.903 | 6.07 | 744000 | 2.9316 |
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- | 2.9057 | 6.13 | 752000 | 2.9447 |
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- | 2.9057 | 6.2 | 760000 | 2.9363 |
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- | 2.9146 | 6.26 | 768000 | 2.9438 |
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- | 2.9146 | 6.33 | 776000 | 2.9475 |
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- | 2.9221 | 6.39 | 784000 | 2.9394 |
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- | 2.9221 | 6.46 | 792000 | 2.9371 |
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- | 2.9316 | 6.52 | 800000 | 2.9494 |
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- | 2.9316 | 6.59 | 808000 | 2.9727 |
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- | 2.9421 | 6.65 | 816000 | 2.9759 |
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- | 2.9421 | 6.72 | 824000 | 2.9665 |
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- | 2.9538 | 6.78 | 832000 | 2.9650 |
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- | 2.9538 | 6.85 | 840000 | 2.9761 |
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- | 2.9594 | 6.91 | 848000 | 2.9901 |
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- | 2.9594 | 6.98 | 856000 | 2.9732 |
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- | 2.9564 | 7.05 | 864000 | 2.9897 |
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- | 2.9564 | 7.11 | 872000 | 2.9801 |
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- | 2.9561 | 7.18 | 880000 | 2.9839 |
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- | 2.9561 | 7.24 | 888000 | 2.9888 |
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- | 2.9669 | 7.31 | 896000 | 3.0000 |
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- | 2.9669 | 7.37 | 904000 | 2.9786 |
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- | 2.9649 | 7.44 | 912000 | 2.9946 |
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- | 2.9649 | 7.5 | 920000 | 3.0002 |
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- | 2.9665 | 7.57 | 928000 | 2.9960 |
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- | 2.9665 | 7.63 | 936000 | 3.0068 |
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- | 2.9708 | 7.7 | 944000 | 2.9938 |
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- | 2.9708 | 7.76 | 952000 | 3.0126 |
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- | 2.981 | 7.83 | 960000 | 2.9959 |
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- | 2.981 | 7.89 | 968000 | 2.9960 |
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- | 2.9805 | 7.96 | 976000 | 2.9919 |
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- | 2.9805 | 8.02 | 984000 | 3.0058 |
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- | 2.9705 | 8.09 | 992000 | 3.0232 |
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- | 2.9705 | 8.15 | 1000000 | 3.0047 |
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- | 2.9715 | 8.22 | 1008000 | 3.0069 |
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- | 2.9715 | 8.28 | 1016000 | 3.0019 |
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- | 2.9695 | 8.35 | 1024000 | 3.0216 |
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- | 2.9695 | 8.41 | 1032000 | 3.0219 |
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- | 2.9762 | 8.48 | 1040000 | 3.0182 |
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- | 2.9762 | 8.55 | 1048000 | 3.0332 |
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- | 2.9786 | 8.61 | 1056000 | 3.0017 |
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- | 2.9786 | 8.68 | 1064000 | 3.0236 |
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- | 2.9889 | 8.74 | 1072000 | 3.0273 |
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- | 2.9889 | 8.81 | 1080000 | 3.0197 |
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- | 2.9842 | 8.87 | 1088000 | 3.0376 |
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- | 2.9842 | 8.94 | 1096000 | 3.0323 |
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- | 2.9912 | 9.0 | 1104000 | 3.0317 |
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- | 2.9912 | 9.07 | 1112000 | 3.0225 |
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- | 2.9919 | 9.13 | 1120000 | 3.0361 |
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- | 2.9919 | 9.2 | 1128000 | 3.0432 |
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- | 2.9872 | 9.26 | 1136000 | 3.0307 |
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- | 2.9872 | 9.33 | 1144000 | 3.0482 |
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- | 2.9823 | 9.39 | 1152000 | 3.0354 |
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- | 2.9823 | 9.46 | 1160000 | 3.0419 |
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- | 2.9882 | 9.52 | 1168000 | 3.0567 |
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- | 2.9882 | 9.59 | 1176000 | 3.0395 |
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- | 3.0079 | 9.65 | 1184000 | 3.0572 |
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- | 3.0079 | 9.72 | 1192000 | 3.0403 |
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- | 3.0243 | 9.78 | 1200000 | 3.0472 |
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- | 3.0243 | 9.85 | 1208000 | 3.0523 |
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- | 3.0127 | 9.92 | 1216000 | 3.0534 |
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- | 3.0127 | 9.98 | 1224000 | 3.0434 |
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- | 3.0106 | 10.05 | 1232000 | 3.0687 |
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- | 3.0106 | 10.11 | 1240000 | 3.0678 |
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- | 3.0063 | 10.18 | 1248000 | 3.0652 |
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- | 3.0063 | 10.24 | 1256000 | 3.0768 |
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- | 3.0187 | 10.31 | 1264000 | 3.0692 |
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- | 3.0187 | 10.37 | 1272000 | 3.0621 |
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- | 3.0202 | 10.44 | 1280000 | 3.0663 |
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- | 3.0202 | 10.5 | 1288000 | 3.0537 |
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- | 3.0219 | 10.57 | 1296000 | 3.0725 |
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- | 3.0219 | 10.63 | 1304000 | 3.0664 |
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- | 3.0232 | 10.7 | 1312000 | 3.0724 |
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- | 3.0232 | 10.76 | 1320000 | 3.0476 |
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- | 3.0247 | 10.83 | 1328000 | 3.0729 |
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- | 3.0247 | 10.89 | 1336000 | 3.0646 |
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- | 3.0335 | 10.96 | 1344000 | 3.0604 |
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- | 3.0335 | 11.02 | 1352000 | 3.0631 |
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- | 3.0182 | 11.09 | 1360000 | 3.0669 |
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- | 3.0182 | 11.15 | 1368000 | 3.0626 |
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- | 3.0124 | 11.22 | 1376000 | 3.0535 |
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- | 3.0124 | 11.29 | 1384000 | 3.0768 |
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- | 3.016 | 11.35 | 1392000 | 3.0615 |
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- | 3.016 | 11.42 | 1400000 | 3.0689 |
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- | 3.0133 | 11.48 | 1408000 | 3.0699 |
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- | 3.0133 | 11.55 | 1416000 | 3.0647 |
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- | 3.0227 | 11.61 | 1424000 | 3.0705 |
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- | 3.0227 | 11.68 | 1432000 | 3.0706 |
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- | 3.0267 | 11.74 | 1440000 | 3.0694 |
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- | 3.0267 | 11.81 | 1448000 | 3.0721 |
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- | 3.021 | 11.87 | 1456000 | 3.0690 |
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- | 3.021 | 11.94 | 1464000 | 3.0603 |
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- | 3.0144 | 12.0 | 1472000 | 3.0658 |
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- | 3.0144 | 12.07 | 1480000 | 3.0720 |
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- | 3.0204 | 12.13 | 1488000 | 3.0668 |
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- | 3.0204 | 12.2 | 1496000 | 3.0773 |
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- | 3.0085 | 12.26 | 1504000 | 3.0848 |
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- | 3.0085 | 12.33 | 1512000 | 3.0568 |
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- | 3.0146 | 12.39 | 1520000 | 3.0783 |
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- | 3.0146 | 12.46 | 1528000 | 3.0736 |
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- | 3.02 | 12.52 | 1536000 | 3.0534 |
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- | 3.02 | 12.59 | 1544000 | 3.0684 |
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- | 3.0229 | 12.65 | 1552000 | 3.0767 |
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- | 3.0229 | 12.72 | 1560000 | 3.0569 |
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- | 3.0152 | 12.79 | 1568000 | 3.0788 |
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- | 3.0152 | 12.85 | 1576000 | 3.0663 |
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- | 3.02 | 12.92 | 1584000 | 3.0670 |
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- | 3.02 | 12.98 | 1592000 | 3.0683 |
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- | 3.0128 | 13.05 | 1600000 | 3.0718 |
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- | 3.0128 | 13.11 | 1608000 | 3.0847 |
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- | 3.016 | 13.18 | 1616000 | 3.0664 |
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- | 3.016 | 13.24 | 1624000 | 3.0688 |
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- | 3.0007 | 13.31 | 1632000 | 3.0741 |
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- | 3.0007 | 13.37 | 1640000 | 3.0663 |
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- | 3.0241 | 13.44 | 1648000 | 3.0607 |
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- | 3.0241 | 13.5 | 1656000 | 3.0635 |
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- | 3.0103 | 13.57 | 1664000 | 3.0731 |
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- | 3.0103 | 13.63 | 1672000 | 3.0649 |
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- | 3.0188 | 13.7 | 1680000 | 3.0587 |
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- | 3.0188 | 13.76 | 1688000 | 3.0704 |
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- | 3.0217 | 13.83 | 1696000 | 3.0664 |
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- | 3.0217 | 13.89 | 1704000 | 3.0627 |
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- | 3.0282 | 13.96 | 1712000 | 3.0714 |
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- | 3.0282 | 14.02 | 1720000 | 3.0688 |
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- | 3.0166 | 14.09 | 1728000 | 3.0521 |
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- | 3.0166 | 14.16 | 1736000 | 3.0538 |
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- | 3.0134 | 14.22 | 1744000 | 3.0641 |
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- | 3.0134 | 14.29 | 1752000 | 3.0639 |
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- | 3.0032 | 14.35 | 1760000 | 3.0588 |
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- | 3.0032 | 14.42 | 1768000 | 3.0646 |
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- | 3.0136 | 14.48 | 1776000 | 3.0629 |
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- | 3.0136 | 14.55 | 1784000 | 3.0578 |
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- | 3.0086 | 14.61 | 1792000 | 3.0529 |
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- | 3.0086 | 14.68 | 1800000 | 3.0615 |
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- | 3.019 | 14.74 | 1808000 | 3.0566 |
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- | 3.019 | 14.81 | 1816000 | 3.0659 |
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- | 3.024 | 14.87 | 1824000 | 3.0615 |
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- | 3.024 | 14.94 | 1832000 | 3.0530 |
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- | 3.0089 | 15.0 | 1840000 | 3.0797 |
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- | 3.0089 | 15.07 | 1848000 | 3.0700 |
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- | 3.0174 | 15.13 | 1856000 | 3.0748 |
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- | 3.0174 | 15.2 | 1864000 | 3.0643 |
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- | 3.0176 | 15.26 | 1872000 | 3.0628 |
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- | 3.0176 | 15.33 | 1880000 | 3.0630 |
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- | 3.0164 | 15.39 | 1888000 | 3.0722 |
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- | 3.0164 | 15.46 | 1896000 | 3.0744 |
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- | 3.0302 | 15.53 | 1904000 | 3.0739 |
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- | 3.0302 | 15.59 | 1912000 | 3.0700 |
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- | 3.0204 | 15.66 | 1920000 | 3.0751 |
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- | 3.0204 | 15.72 | 1928000 | 3.0598 |
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- | 3.0147 | 15.79 | 1936000 | 3.0522 |
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- | 3.0147 | 15.85 | 1944000 | 3.0655 |
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- | 3.0245 | 15.92 | 1952000 | 3.0569 |
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- | 3.0245 | 15.98 | 1960000 | 3.0623 |
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- | 3.0069 | 16.05 | 1968000 | 3.0600 |
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- | 3.0069 | 16.11 | 1976000 | 3.0639 |
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- | 3.0068 | 16.18 | 1984000 | 3.0775 |
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- | 3.0068 | 16.24 | 1992000 | 3.0669 |
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- | 3.0275 | 16.31 | 2000000 | 3.0627 |
300
- | 3.0275 | 16.37 | 2008000 | 3.0645 |
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- | 3.0164 | 16.44 | 2016000 | 3.0667 |
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- | 3.0164 | 16.5 | 2024000 | 3.0490 |
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- | 3.0148 | 16.57 | 2032000 | 3.0618 |
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- | 3.0148 | 16.63 | 2040000 | 3.0545 |
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- | 3.022 | 16.7 | 2048000 | 3.0651 |
306
- | 3.022 | 16.76 | 2056000 | 3.0687 |
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- | 3.0235 | 16.83 | 2064000 | 3.0516 |
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- | 3.0235 | 16.89 | 2072000 | 3.0761 |
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- | 3.0194 | 16.96 | 2080000 | 3.0807 |
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- | 3.0194 | 17.03 | 2088000 | 3.0601 |
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- | 3.0142 | 17.09 | 2096000 | 3.0721 |
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- | 3.0142 | 17.16 | 2104000 | 3.0653 |
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- | 3.0183 | 17.22 | 2112000 | 3.0617 |
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- | 3.0183 | 17.29 | 2120000 | 3.0622 |
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- | 3.0092 | 17.35 | 2128000 | 3.0682 |
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- | 3.0092 | 17.42 | 2136000 | 3.0732 |
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- | 3.0071 | 17.48 | 2144000 | 3.0763 |
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- | 3.0071 | 17.55 | 2152000 | 3.0675 |
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- | 3.0272 | 17.61 | 2160000 | 3.0671 |
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- | 3.0272 | 17.68 | 2168000 | 3.0622 |
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- | 3.0235 | 17.74 | 2176000 | 3.0789 |
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- | 3.0235 | 17.81 | 2184000 | 3.0623 |
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- | 3.0179 | 17.87 | 2192000 | 3.0784 |
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- | 3.0179 | 17.94 | 2200000 | 3.0629 |
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- | 3.0209 | 18.0 | 2208000 | 3.0731 |
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- | 3.0209 | 18.07 | 2216000 | 3.0946 |
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- | 3.0237 | 18.13 | 2224000 | 3.0653 |
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- | 3.0237 | 18.2 | 2232000 | 3.0590 |
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- | 3.0164 | 18.26 | 2240000 | 3.0707 |
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- | 3.0164 | 18.33 | 2248000 | 3.0546 |
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- | 3.0206 | 18.4 | 2256000 | 3.0742 |
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- | 3.0206 | 18.46 | 2264000 | 3.0793 |
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- | 3.0138 | 18.53 | 2272000 | 3.0560 |
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- | 3.0138 | 18.59 | 2280000 | 3.0870 |
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- | 3.0377 | 18.66 | 2288000 | 3.0742 |
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- | 3.0377 | 18.72 | 2296000 | 3.0676 |
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- | 3.0227 | 18.79 | 2304000 | 3.0625 |
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- | 3.0227 | 18.85 | 2312000 | 3.0736 |
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- | 3.0359 | 18.92 | 2320000 | 3.0801 |
340
- | 3.0359 | 18.98 | 2328000 | 3.0710 |
341
- | 3.0248 | 19.05 | 2336000 | 3.0692 |
342
- | 3.0248 | 19.11 | 2344000 | 3.0677 |
343
- | 3.0235 | 19.18 | 2352000 | 3.0896 |
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- | 3.0235 | 19.24 | 2360000 | 3.0778 |
345
- | 3.0187 | 19.31 | 2368000 | 3.0700 |
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- | 3.0187 | 19.37 | 2376000 | 3.0743 |
347
- | 3.0189 | 19.44 | 2384000 | 3.0780 |
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- | 3.0189 | 19.5 | 2392000 | 3.0867 |
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- | 3.0184 | 19.57 | 2400000 | 3.0793 |
350
 
351
 
352
  ### Framework versions
 
1
  ---
2
+ base_model: vinai/bertweet-base
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: bertweet-2020-Q1-filtered
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # bertweet-2020-Q1-filtered
14
 
15
+ This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 3.3321
18
 
19
  ## Model description
20
 
 
46
 
47
  | Training Loss | Epoch | Step | Validation Loss |
48
  |:-------------:|:-----:|:-------:|:---------------:|
49
+ | No log | 0.07 | 8000 | 2.6350 |
50
+ | 2.7848 | 0.13 | 16000 | 2.6556 |
51
+ | 2.7848 | 0.2 | 24000 | 2.6695 |
52
+ | 2.7545 | 0.26 | 32000 | 2.6713 |
53
+ | 2.7545 | 0.33 | 40000 | 2.7089 |
54
+ | 2.7717 | 0.39 | 48000 | 2.7144 |
55
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56
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57
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66
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103
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112
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113
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117
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119
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120
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121
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128
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129
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143
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144
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145
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146
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147
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148
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149
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150
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151
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155
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156
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157
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158
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159
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168
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169
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170
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177
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180
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183
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184
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186
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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198
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199
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200
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201
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202
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203
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205
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210
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211
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214
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216
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217
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218
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219
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220
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221
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223
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224
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225
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229
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230
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233
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234
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235
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236
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239
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240
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243
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244
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245
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246
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248
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249
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254
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255
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256
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257
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258
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259
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260
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261
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262
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263
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264
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265
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266
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267
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268
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269
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270
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271
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272
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273
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274
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275
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276
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277
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278
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279
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280
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281
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282
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283
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284
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285
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286
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287
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288
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289
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290
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291
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292
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293
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294
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295
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296
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297
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298
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299
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305
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306
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309
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310
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311
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312
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313
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314
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315
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316
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317
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318
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319
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320
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321
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322
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323
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324
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325
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326
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327
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328
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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341
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342
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343
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344
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345
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347
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348
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349
 
350
 
351
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