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--- |
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license: mit |
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base_model: DouglasPontes/2020-Q3-50p-filtered-random |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: 2020-Q4-50p-filtered-random-prog_from_Q3 |
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results: [] |
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--- |
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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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# 2020-Q4-50p-filtered-random-prog_from_Q3 |
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This model is a fine-tuned version of [DouglasPontes/2020-Q3-50p-filtered-random](https://huggingface.co/DouglasPontes/2020-Q3-50p-filtered-random) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2730 |
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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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- learning_rate: 4.1e-07 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 2400000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-------:|:---------------:| |
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| No log | 0.03 | 8000 | 2.3816 | |
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| 2.5089 | 0.07 | 16000 | 2.3647 | |
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| 2.5089 | 0.1 | 24000 | 2.3552 | |
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| 2.4989 | 0.13 | 32000 | 2.3528 | |
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| 2.4989 | 0.17 | 40000 | 2.3486 | |
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| 2.4836 | 0.2 | 48000 | 2.3463 | |
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| 2.4836 | 0.24 | 56000 | 2.3411 | |
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| 2.4904 | 0.27 | 64000 | 2.3394 | |
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| 2.4904 | 0.3 | 72000 | 2.3350 | |
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| 2.4733 | 0.34 | 80000 | 2.3309 | |
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| 2.4733 | 0.37 | 88000 | 2.3289 | |
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| 2.4675 | 0.4 | 96000 | 2.3381 | |
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| 2.4675 | 0.44 | 104000 | 2.3317 | |
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| 2.4762 | 0.47 | 112000 | 2.3218 | |
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| 2.4762 | 0.51 | 120000 | 2.3267 | |
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| 2.4616 | 0.54 | 128000 | 2.3241 | |
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| 2.4616 | 0.57 | 136000 | 2.3281 | |
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| 2.4601 | 0.61 | 144000 | 2.3152 | |
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| 2.4601 | 0.64 | 152000 | 2.3243 | |
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| 2.4563 | 0.67 | 160000 | 2.3202 | |
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| 2.4563 | 0.71 | 168000 | 2.3193 | |
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| 2.459 | 0.74 | 176000 | 2.3182 | |
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| 2.459 | 0.77 | 184000 | 2.3247 | |
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| 2.4639 | 0.81 | 192000 | 2.3201 | |
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| 2.4639 | 0.84 | 200000 | 2.3243 | |
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| 2.4561 | 0.88 | 208000 | 2.3218 | |
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| 2.4561 | 0.91 | 216000 | 2.3137 | |
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| 2.4556 | 0.94 | 224000 | 2.3180 | |
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| 2.4556 | 0.98 | 232000 | 2.3147 | |
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| 2.4573 | 1.01 | 240000 | 2.3100 | |
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| 2.4573 | 1.04 | 248000 | 2.3118 | |
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| 2.4516 | 1.08 | 256000 | 2.3158 | |
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| 2.4516 | 1.11 | 264000 | 2.3133 | |
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| 2.4561 | 1.15 | 272000 | 2.3065 | |
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| 2.4561 | 1.18 | 280000 | 2.3183 | |
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| 2.4476 | 1.21 | 288000 | 2.3106 | |
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| 2.4476 | 1.25 | 296000 | 2.3131 | |
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| 2.4503 | 1.28 | 304000 | 2.3104 | |
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| 2.4503 | 1.31 | 312000 | 2.3101 | |
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| 2.4495 | 1.35 | 320000 | 2.3086 | |
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| 2.4495 | 1.38 | 328000 | 2.3057 | |
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| 2.4534 | 1.41 | 336000 | 2.3086 | |
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| 2.4534 | 1.45 | 344000 | 2.3093 | |
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| 2.4486 | 1.48 | 352000 | 2.3018 | |
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| 2.4486 | 1.52 | 360000 | 2.3060 | |
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| 2.4457 | 1.55 | 368000 | 2.3083 | |
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| 2.4457 | 1.58 | 376000 | 2.3110 | |
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| 2.4443 | 1.62 | 384000 | 2.2975 | |
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| 2.4443 | 1.65 | 392000 | 2.3009 | |
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| 2.4405 | 1.68 | 400000 | 2.3067 | |
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| 2.4405 | 1.72 | 408000 | 2.3027 | |
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| 2.4531 | 1.75 | 416000 | 2.3050 | |
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| 2.4531 | 1.79 | 424000 | 2.3026 | |
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| 2.4539 | 1.82 | 432000 | 2.2929 | |
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| 2.4539 | 1.85 | 440000 | 2.3051 | |
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| 2.4499 | 1.89 | 448000 | 2.3035 | |
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| 2.4499 | 1.92 | 456000 | 2.3011 | |
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| 2.4401 | 1.95 | 464000 | 2.2920 | |
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| 2.4401 | 1.99 | 472000 | 2.2999 | |
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| 2.4401 | 2.02 | 480000 | 2.3034 | |
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| 2.4401 | 2.05 | 488000 | 2.3021 | |
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| 2.4433 | 2.09 | 496000 | 2.3102 | |
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| 2.4433 | 2.12 | 504000 | 2.2985 | |
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| 2.4445 | 2.16 | 512000 | 2.3018 | |
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| 2.4445 | 2.19 | 520000 | 2.2996 | |
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| 2.4379 | 2.22 | 528000 | 2.3006 | |
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| 2.4379 | 2.26 | 536000 | 2.2970 | |
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| 2.4454 | 2.29 | 544000 | 2.3014 | |
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| 2.4454 | 2.32 | 552000 | 2.2992 | |
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| 2.4457 | 2.36 | 560000 | 2.2962 | |
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| 2.4457 | 2.39 | 568000 | 2.3009 | |
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| 2.4354 | 2.43 | 576000 | 2.2960 | |
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| 2.4354 | 2.46 | 584000 | 2.3008 | |
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| 2.4361 | 2.49 | 592000 | 2.2898 | |
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| 2.4361 | 2.53 | 600000 | 2.3060 | |
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| 2.4377 | 2.56 | 608000 | 2.2990 | |
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| 2.4377 | 2.59 | 616000 | 2.2989 | |
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| 2.4416 | 2.63 | 624000 | 2.2969 | |
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| 2.4416 | 2.66 | 632000 | 2.2933 | |
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| 2.434 | 2.69 | 640000 | 2.2998 | |
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| 2.434 | 2.73 | 648000 | 2.2948 | |
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| 2.433 | 2.76 | 656000 | 2.2892 | |
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| 2.433 | 2.8 | 664000 | 2.2929 | |
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| 2.44 | 2.83 | 672000 | 2.2973 | |
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| 2.44 | 2.86 | 680000 | 2.2926 | |
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| 2.4291 | 2.9 | 688000 | 2.2990 | |
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| 2.4291 | 2.93 | 696000 | 2.2937 | |
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| 2.4336 | 2.96 | 704000 | 2.2894 | |
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| 2.4336 | 3.0 | 712000 | 2.2958 | |
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| 2.439 | 3.03 | 720000 | 2.2956 | |
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| 2.439 | 3.07 | 728000 | 2.2928 | |
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| 2.4405 | 3.1 | 736000 | 2.2956 | |
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| 2.4405 | 3.13 | 744000 | 2.2905 | |
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| 2.4332 | 3.17 | 752000 | 2.2921 | |
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| 2.4332 | 3.2 | 760000 | 2.2907 | |
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| 2.4353 | 3.23 | 768000 | 2.2879 | |
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| 2.4353 | 3.27 | 776000 | 2.2929 | |
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| 2.4273 | 3.3 | 784000 | 2.2953 | |
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| 2.4273 | 3.33 | 792000 | 2.2917 | |
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| 2.4233 | 3.37 | 800000 | 2.2947 | |
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| 2.4233 | 3.4 | 808000 | 2.2943 | |
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| 2.4324 | 3.44 | 816000 | 2.2940 | |
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| 2.4324 | 3.47 | 824000 | 2.2911 | |
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| 2.4461 | 3.5 | 832000 | 2.2920 | |
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| 2.4461 | 3.54 | 840000 | 2.2911 | |
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| 2.4267 | 3.57 | 848000 | 2.2940 | |
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| 2.4267 | 3.6 | 856000 | 2.2890 | |
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| 2.4313 | 3.64 | 864000 | 2.2913 | |
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| 2.4313 | 3.67 | 872000 | 2.2967 | |
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| 2.4388 | 3.71 | 880000 | 2.2907 | |
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| 2.4388 | 3.74 | 888000 | 2.2952 | |
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| 2.4326 | 3.77 | 896000 | 2.2873 | |
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| 2.4326 | 3.81 | 904000 | 2.2871 | |
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| 2.4312 | 3.84 | 912000 | 2.2880 | |
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| 2.4312 | 3.87 | 920000 | 2.2941 | |
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| 2.4398 | 3.91 | 928000 | 2.2925 | |
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| 2.4398 | 3.94 | 936000 | 2.2965 | |
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| 2.441 | 3.97 | 944000 | 2.2890 | |
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| 2.441 | 4.01 | 952000 | 2.2946 | |
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| 2.4345 | 4.04 | 960000 | 2.2910 | |
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| 2.4345 | 4.08 | 968000 | 2.2792 | |
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| 2.4332 | 4.11 | 976000 | 2.2856 | |
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| 2.4332 | 4.14 | 984000 | 2.2879 | |
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| 2.4375 | 4.18 | 992000 | 2.2861 | |
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| 2.4375 | 4.21 | 1000000 | 2.2892 | |
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| 2.4282 | 4.24 | 1008000 | 2.2894 | |
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| 2.4282 | 4.28 | 1016000 | 2.2902 | |
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| 2.4231 | 4.31 | 1024000 | 2.2830 | |
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| 2.4231 | 4.35 | 1032000 | 2.2948 | |
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| 2.4299 | 4.38 | 1040000 | 2.2915 | |
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| 2.4299 | 4.41 | 1048000 | 2.2922 | |
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| 2.4353 | 4.45 | 1056000 | 2.2876 | |
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| 2.4353 | 4.48 | 1064000 | 2.2893 | |
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| 2.4308 | 4.51 | 1072000 | 2.2920 | |
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| 2.4308 | 4.55 | 1080000 | 2.2860 | |
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| 2.4358 | 4.58 | 1088000 | 2.2907 | |
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| 2.4358 | 4.61 | 1096000 | 2.2808 | |
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| 2.4341 | 4.65 | 1104000 | 2.2902 | |
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| 2.4341 | 4.68 | 1112000 | 2.2815 | |
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| 2.4315 | 4.72 | 1120000 | 2.2961 | |
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| 2.4315 | 4.75 | 1128000 | 2.2885 | |
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| 2.434 | 4.78 | 1136000 | 2.2917 | |
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| 2.434 | 4.82 | 1144000 | 2.2851 | |
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| 2.4324 | 4.85 | 1152000 | 2.2837 | |
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| 2.4324 | 4.88 | 1160000 | 2.2883 | |
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| 2.4297 | 4.92 | 1168000 | 2.2824 | |
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| 2.4297 | 4.95 | 1176000 | 2.2832 | |
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| 2.436 | 4.99 | 1184000 | 2.2865 | |
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| 2.436 | 5.02 | 1192000 | 2.2816 | |
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| 2.4329 | 5.05 | 1200000 | 2.2862 | |
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| 2.4329 | 5.09 | 1208000 | 2.2847 | |
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| 2.4276 | 5.12 | 1216000 | 2.2951 | |
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| 2.4276 | 5.15 | 1224000 | 2.2980 | |
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| 2.4362 | 5.19 | 1232000 | 2.2889 | |
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| 2.4362 | 5.22 | 1240000 | 2.2914 | |
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| 2.4309 | 5.25 | 1248000 | 2.2915 | |
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| 2.4309 | 5.29 | 1256000 | 2.2822 | |
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| 2.4414 | 5.32 | 1264000 | 2.2871 | |
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| 2.4414 | 5.36 | 1272000 | 2.2890 | |
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| 2.4241 | 5.39 | 1280000 | 2.2844 | |
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| 2.4241 | 5.42 | 1288000 | 2.2812 | |
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| 2.4251 | 5.46 | 1296000 | 2.2874 | |
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| 2.4251 | 5.49 | 1304000 | 2.2846 | |
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| 2.4318 | 5.52 | 1312000 | 2.2831 | |
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| 2.4318 | 5.56 | 1320000 | 2.2895 | |
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| 2.4247 | 5.59 | 1328000 | 2.2796 | |
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| 2.4247 | 5.63 | 1336000 | 2.2834 | |
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| 2.4305 | 5.66 | 1344000 | 2.2811 | |
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| 2.4305 | 5.69 | 1352000 | 2.2922 | |
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| 2.4336 | 5.73 | 1360000 | 2.2830 | |
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| 2.4336 | 5.76 | 1368000 | 2.2904 | |
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| 2.428 | 5.79 | 1376000 | 2.2843 | |
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| 2.428 | 5.83 | 1384000 | 2.2804 | |
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| 2.4254 | 5.86 | 1392000 | 2.2852 | |
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| 2.4254 | 5.89 | 1400000 | 2.2858 | |
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| 2.4287 | 5.93 | 1408000 | 2.2922 | |
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| 2.4287 | 5.96 | 1416000 | 2.2847 | |
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| 2.4291 | 6.0 | 1424000 | 2.2856 | |
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| 2.4291 | 6.03 | 1432000 | 2.2876 | |
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| 2.4289 | 6.06 | 1440000 | 2.2822 | |
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| 2.4289 | 6.1 | 1448000 | 2.2787 | |
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| 2.4272 | 6.13 | 1456000 | 2.2811 | |
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| 2.4272 | 6.16 | 1464000 | 2.2853 | |
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| 2.4267 | 6.2 | 1472000 | 2.2818 | |
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| 2.4267 | 6.23 | 1480000 | 2.2765 | |
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| 2.4237 | 6.27 | 1488000 | 2.2791 | |
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| 2.4237 | 6.3 | 1496000 | 2.2768 | |
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| 2.4277 | 6.33 | 1504000 | 2.2866 | |
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| 2.4277 | 6.37 | 1512000 | 2.2821 | |
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| 2.4316 | 6.4 | 1520000 | 2.2856 | |
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| 2.4316 | 6.43 | 1528000 | 2.2820 | |
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| 2.4222 | 6.47 | 1536000 | 2.2891 | |
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| 2.4222 | 6.5 | 1544000 | 2.2803 | |
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| 2.426 | 6.53 | 1552000 | 2.2797 | |
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| 2.426 | 6.57 | 1560000 | 2.2844 | |
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| 2.422 | 6.6 | 1568000 | 2.2872 | |
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| 2.422 | 6.64 | 1576000 | 2.2904 | |
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| 2.4323 | 6.67 | 1584000 | 2.2797 | |
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| 2.4323 | 6.7 | 1592000 | 2.2757 | |
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| 2.4315 | 6.74 | 1600000 | 2.2874 | |
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| 2.4315 | 6.77 | 1608000 | 2.2763 | |
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| 2.421 | 6.8 | 1616000 | 2.2857 | |
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| 2.421 | 6.84 | 1624000 | 2.2804 | |
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| 2.4299 | 6.87 | 1632000 | 2.2825 | |
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| 2.4299 | 6.91 | 1640000 | 2.2819 | |
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| 2.4289 | 6.94 | 1648000 | 2.2824 | |
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| 2.4289 | 6.97 | 1656000 | 2.2821 | |
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| 2.4257 | 7.01 | 1664000 | 2.2802 | |
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| 2.4257 | 7.04 | 1672000 | 2.2760 | |
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| 2.4227 | 7.07 | 1680000 | 2.2810 | |
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| 2.4227 | 7.11 | 1688000 | 2.2777 | |
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| 2.4287 | 7.14 | 1696000 | 2.2772 | |
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| 2.4287 | 7.17 | 1704000 | 2.2786 | |
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| 2.4227 | 7.21 | 1712000 | 2.2859 | |
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| 2.4227 | 7.24 | 1720000 | 2.2862 | |
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| 2.4262 | 7.28 | 1728000 | 2.2789 | |
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| 2.4262 | 7.31 | 1736000 | 2.2848 | |
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| 2.4263 | 7.34 | 1744000 | 2.2754 | |
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| 2.4263 | 7.38 | 1752000 | 2.2778 | |
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| 2.4246 | 7.41 | 1760000 | 2.2735 | |
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| 2.4246 | 7.44 | 1768000 | 2.2827 | |
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| 2.4147 | 7.48 | 1776000 | 2.2850 | |
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| 2.4147 | 7.51 | 1784000 | 2.2821 | |
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| 2.4288 | 7.55 | 1792000 | 2.2803 | |
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| 2.4288 | 7.58 | 1800000 | 2.2760 | |
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| 2.4231 | 7.61 | 1808000 | 2.2749 | |
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| 2.4231 | 7.65 | 1816000 | 2.2749 | |
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| 2.4243 | 7.68 | 1824000 | 2.2743 | |
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| 2.4243 | 7.71 | 1832000 | 2.2792 | |
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| 2.4215 | 7.75 | 1840000 | 2.2752 | |
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| 2.4215 | 7.78 | 1848000 | 2.2770 | |
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| 2.4213 | 7.81 | 1856000 | 2.2802 | |
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| 2.4213 | 7.85 | 1864000 | 2.2796 | |
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| 2.4236 | 7.88 | 1872000 | 2.2883 | |
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| 2.4236 | 7.92 | 1880000 | 2.2792 | |
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| 2.4237 | 7.95 | 1888000 | 2.2726 | |
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| 2.4237 | 7.98 | 1896000 | 2.2816 | |
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| 2.4183 | 8.02 | 1904000 | 2.2790 | |
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| 2.4183 | 8.05 | 1912000 | 2.2815 | |
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| 2.4215 | 8.08 | 1920000 | 2.2774 | |
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| 2.4215 | 8.12 | 1928000 | 2.2700 | |
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| 2.4258 | 8.15 | 1936000 | 2.2763 | |
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| 2.4258 | 8.19 | 1944000 | 2.2786 | |
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| 2.4209 | 8.22 | 1952000 | 2.2763 | |
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| 2.4209 | 8.25 | 1960000 | 2.2789 | |
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| 2.4217 | 8.29 | 1968000 | 2.2784 | |
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| 2.4217 | 8.32 | 1976000 | 2.2773 | |
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| 2.4279 | 8.35 | 1984000 | 2.2861 | |
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| 2.4279 | 8.39 | 1992000 | 2.2728 | |
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| 2.4268 | 8.42 | 2000000 | 2.2762 | |
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| 2.4268 | 8.45 | 2008000 | 2.2789 | |
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| 2.4177 | 8.49 | 2016000 | 2.2822 | |
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| 2.4177 | 8.52 | 2024000 | 2.2759 | |
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| 2.4166 | 8.56 | 2032000 | 2.2792 | |
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| 2.4166 | 8.59 | 2040000 | 2.2721 | |
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| 2.4223 | 8.62 | 2048000 | 2.2768 | |
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| 2.4223 | 8.66 | 2056000 | 2.2726 | |
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| 2.4139 | 8.69 | 2064000 | 2.2825 | |
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| 2.4139 | 8.72 | 2072000 | 2.2739 | |
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| 2.4236 | 8.76 | 2080000 | 2.2834 | |
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| 2.4236 | 8.79 | 2088000 | 2.2750 | |
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| 2.4235 | 8.83 | 2096000 | 2.2752 | |
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| 2.4235 | 8.86 | 2104000 | 2.2803 | |
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| 2.4193 | 8.89 | 2112000 | 2.2763 | |
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| 2.4193 | 8.93 | 2120000 | 2.2755 | |
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| 2.4179 | 8.96 | 2128000 | 2.2794 | |
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| 2.4179 | 8.99 | 2136000 | 2.2711 | |
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| 2.4181 | 9.03 | 2144000 | 2.2792 | |
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| 2.4181 | 9.06 | 2152000 | 2.2752 | |
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| 2.4173 | 9.09 | 2160000 | 2.2775 | |
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| 2.4173 | 9.13 | 2168000 | 2.2752 | |
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| 2.4242 | 9.16 | 2176000 | 2.2729 | |
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| 2.4242 | 9.2 | 2184000 | 2.2793 | |
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| 2.4166 | 9.23 | 2192000 | 2.2719 | |
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| 2.4166 | 9.26 | 2200000 | 2.2820 | |
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| 2.4181 | 9.3 | 2208000 | 2.2716 | |
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| 2.4181 | 9.33 | 2216000 | 2.2855 | |
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| 2.4245 | 9.36 | 2224000 | 2.2805 | |
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| 2.4245 | 9.4 | 2232000 | 2.2721 | |
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| 2.4204 | 9.43 | 2240000 | 2.2707 | |
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| 2.4204 | 9.47 | 2248000 | 2.2767 | |
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| 2.4255 | 9.5 | 2256000 | 2.2710 | |
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| 2.4255 | 9.53 | 2264000 | 2.2814 | |
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| 2.4254 | 9.57 | 2272000 | 2.2746 | |
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| 2.4254 | 9.6 | 2280000 | 2.2766 | |
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| 2.4232 | 9.63 | 2288000 | 2.2725 | |
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| 2.4232 | 9.67 | 2296000 | 2.2765 | |
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| 2.4189 | 9.7 | 2304000 | 2.2756 | |
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| 2.4189 | 9.73 | 2312000 | 2.2768 | |
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| 2.4105 | 9.77 | 2320000 | 2.2804 | |
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| 2.4105 | 9.8 | 2328000 | 2.2873 | |
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| 2.415 | 9.84 | 2336000 | 2.2783 | |
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| 2.415 | 9.87 | 2344000 | 2.2737 | |
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| 2.4174 | 9.9 | 2352000 | 2.2786 | |
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| 2.4174 | 9.94 | 2360000 | 2.2730 | |
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| 2.4199 | 9.97 | 2368000 | 2.2794 | |
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| 2.4199 | 10.0 | 2376000 | 2.2848 | |
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| 2.4224 | 10.04 | 2384000 | 2.2811 | |
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| 2.4224 | 10.07 | 2392000 | 2.2818 | |
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| 2.4226 | 10.11 | 2400000 | 2.2798 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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