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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: MIX3_ja-en_helsinki |
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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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# MIX3_ja-en_helsinki |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ja-en](https://huggingface.co/Helsinki-NLP/opus-mt-ja-en) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4832 |
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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: 0.0003 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-------:|:---------------:| |
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| 2.8699 | 0.01 | 5000 | 2.3465 | |
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| 2.6168 | 0.02 | 10000 | 2.2205 | |
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| 2.5083 | 0.03 | 15000 | 2.2382 | |
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| 2.4359 | 0.04 | 20000 | 2.1670 | |
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| 2.3821 | 0.06 | 25000 | 2.1122 | |
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| 2.3358 | 0.07 | 30000 | 2.0902 | |
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| 2.3045 | 0.08 | 35000 | 2.0461 | |
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| 2.2782 | 0.09 | 40000 | 2.0290 | |
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| 2.2481 | 0.1 | 45000 | 1.9910 | |
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| 2.2267 | 0.11 | 50000 | 2.0059 | |
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| 2.2056 | 0.12 | 55000 | 1.9858 | |
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| 2.1903 | 0.13 | 60000 | 1.9725 | |
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| 2.173 | 0.15 | 65000 | 1.9797 | |
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| 2.154 | 0.16 | 70000 | 1.9654 | |
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| 2.1429 | 0.17 | 75000 | 1.9567 | |
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| 2.1304 | 0.18 | 80000 | 1.9348 | |
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| 2.1232 | 0.19 | 85000 | 1.9361 | |
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| 2.116 | 0.2 | 90000 | 1.9277 | |
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| 2.1016 | 0.21 | 95000 | 1.9193 | |
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| 2.0984 | 0.22 | 100000 | 1.9064 | |
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| 2.0797 | 0.24 | 105000 | 1.9177 | |
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| 2.0767 | 0.25 | 110000 | 1.8975 | |
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| 2.0642 | 0.26 | 115000 | 1.8782 | |
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| 2.0595 | 0.27 | 120000 | 1.9012 | |
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| 2.0533 | 0.28 | 125000 | 1.8977 | |
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| 2.044 | 0.29 | 130000 | 1.8984 | |
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| 2.0374 | 0.3 | 135000 | 1.9221 | |
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| 2.0305 | 0.31 | 140000 | 1.9243 | |
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| 2.02 | 0.32 | 145000 | 1.8773 | |
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| 2.0195 | 0.34 | 150000 | 1.8676 | |
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| 2.0151 | 0.35 | 155000 | 1.8637 | |
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| 2.0065 | 0.36 | 160000 | 1.8556 | |
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| 2.0037 | 0.37 | 165000 | 1.8399 | |
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| 1.9963 | 0.38 | 170000 | 1.8452 | |
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| 1.9878 | 0.39 | 175000 | 1.8644 | |
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| 1.9871 | 0.4 | 180000 | 1.8576 | |
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| 1.9779 | 0.41 | 185000 | 1.8509 | |
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| 1.9721 | 0.43 | 190000 | 1.8405 | |
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| 1.9724 | 0.44 | 195000 | 1.8594 | |
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| 1.9685 | 0.45 | 200000 | 1.8540 | |
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| 1.9634 | 0.46 | 205000 | 1.8694 | |
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| 1.9583 | 0.47 | 210000 | 1.8591 | |
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| 1.9557 | 0.48 | 215000 | 1.8539 | |
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| 1.9494 | 0.49 | 220000 | 1.8673 | |
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| 1.9484 | 0.5 | 225000 | 1.8021 | |
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| 1.9395 | 0.52 | 230000 | 1.8309 | |
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| 1.9384 | 0.53 | 235000 | 1.7933 | |
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| 1.937 | 0.54 | 240000 | 1.8199 | |
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| 1.9315 | 0.55 | 245000 | 1.8065 | |
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| 1.9276 | 0.56 | 250000 | 1.7857 | |
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| 1.9248 | 0.57 | 255000 | 1.8207 | |
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| 1.9195 | 0.58 | 260000 | 1.7898 | |
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| 1.9187 | 0.59 | 265000 | 1.8097 | |
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| 1.9138 | 0.6 | 270000 | 1.7909 | |
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| 1.9094 | 0.62 | 275000 | 1.7995 | |
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| 1.9098 | 0.63 | 280000 | 1.8165 | |
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| 1.9038 | 0.64 | 285000 | 1.8132 | |
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| 1.9034 | 0.65 | 290000 | 1.7951 | |
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| 1.899 | 0.66 | 295000 | 1.7880 | |
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| 1.8965 | 0.67 | 300000 | 1.7953 | |
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| 1.8941 | 0.68 | 305000 | 1.7986 | |
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| 1.8919 | 0.69 | 310000 | 1.7964 | |
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| 1.8875 | 0.71 | 315000 | 1.8041 | |
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| 1.884 | 0.72 | 320000 | 1.7764 | |
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| 1.8798 | 0.73 | 325000 | 1.8019 | |
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| 1.8801 | 0.74 | 330000 | 1.7790 | |
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| 1.8809 | 0.75 | 335000 | 1.7849 | |
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| 1.8736 | 0.76 | 340000 | 1.7800 | |
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| 1.8727 | 0.77 | 345000 | 1.7900 | |
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| 1.8722 | 0.78 | 350000 | 1.7727 | |
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| 1.8699 | 0.8 | 355000 | 1.7597 | |
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| 1.8672 | 0.81 | 360000 | 1.7824 | |
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| 1.8638 | 0.82 | 365000 | 1.7674 | |
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| 1.8609 | 0.83 | 370000 | 1.7715 | |
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| 1.8584 | 0.84 | 375000 | 1.7694 | |
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| 1.8568 | 0.85 | 380000 | 1.7776 | |
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| 1.8523 | 0.86 | 385000 | 1.7697 | |
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| 1.8584 | 0.87 | 390000 | 1.7436 | |
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| 1.8474 | 0.88 | 395000 | 1.7644 | |
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| 1.8492 | 0.9 | 400000 | 1.7732 | |
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| 1.8465 | 0.91 | 405000 | 1.7611 | |
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| 1.846 | 0.92 | 410000 | 1.7717 | |
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| 1.8431 | 0.93 | 415000 | 1.7514 | |
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| 1.8402 | 0.94 | 420000 | 1.7353 | |
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| 1.8398 | 0.95 | 425000 | 1.7720 | |
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| 1.8314 | 0.96 | 430000 | 1.7728 | |
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| 1.8322 | 0.97 | 435000 | 1.7491 | |
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| 1.8284 | 0.99 | 440000 | 1.7561 | |
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| 1.8301 | 1.0 | 445000 | 1.7499 | |
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| 1.8182 | 1.01 | 450000 | 1.7514 | |
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| 1.8111 | 1.02 | 455000 | 1.7596 | |
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| 1.8116 | 1.03 | 460000 | 1.7455 | |
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| 1.8098 | 1.04 | 465000 | 1.7495 | |
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| 1.809 | 1.05 | 470000 | 1.7446 | |
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| 1.8088 | 1.06 | 475000 | 1.7290 | |
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| 1.8127 | 1.08 | 480000 | 1.7453 | |
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| 1.8051 | 1.09 | 485000 | 1.7495 | |
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| 1.8026 | 1.1 | 490000 | 1.7453 | |
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| 1.8028 | 1.11 | 495000 | 1.7615 | |
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| 1.8046 | 1.12 | 500000 | 1.7491 | |
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| 1.8052 | 1.13 | 505000 | 1.7280 | |
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| 1.7997 | 1.14 | 510000 | 1.7482 | |
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| 1.7976 | 1.15 | 515000 | 1.7368 | |
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| 1.7981 | 1.16 | 520000 | 1.7354 | |
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| 1.7949 | 1.18 | 525000 | 1.7076 | |
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| 1.7943 | 1.19 | 530000 | 1.7020 | |
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| 1.7911 | 1.2 | 535000 | 1.7121 | |
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| 1.7909 | 1.21 | 540000 | 1.7170 | |
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| 1.7926 | 1.22 | 545000 | 1.7310 | |
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| 1.7856 | 1.23 | 550000 | 1.7218 | |
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| 1.7875 | 1.24 | 555000 | 1.7362 | |
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| 1.7801 | 1.25 | 560000 | 1.7484 | |
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| 1.7854 | 1.27 | 565000 | 1.7466 | |
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| 1.7799 | 1.28 | 570000 | 1.7248 | |
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| 1.7823 | 1.29 | 575000 | 1.7355 | |
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| 1.7765 | 1.3 | 580000 | 1.7188 | |
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| 1.7779 | 1.31 | 585000 | 1.6993 | |
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| 1.7751 | 1.32 | 590000 | 1.7154 | |
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| 1.7762 | 1.33 | 595000 | 1.7348 | |
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| 1.7725 | 1.34 | 600000 | 1.7272 | |
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| 1.7701 | 1.36 | 605000 | 1.7157 | |
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| 1.7644 | 1.37 | 610000 | 1.7161 | |
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| 1.7707 | 1.38 | 615000 | 1.6961 | |
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| 1.764 | 1.39 | 620000 | 1.6930 | |
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| 1.7639 | 1.4 | 625000 | 1.6927 | |
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| 1.7654 | 1.41 | 630000 | 1.6989 | |
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| 1.7623 | 1.42 | 635000 | 1.6892 | |
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| 1.7598 | 1.43 | 640000 | 1.6911 | |
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| 1.7575 | 1.44 | 645000 | 1.7199 | |
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| 1.7574 | 1.46 | 650000 | 1.6992 | |
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| 1.7526 | 1.47 | 655000 | 1.6981 | |
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| 1.7556 | 1.48 | 660000 | 1.6860 | |
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| 1.7558 | 1.49 | 665000 | 1.7099 | |
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| 1.7539 | 1.5 | 670000 | 1.6950 | |
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| 1.7454 | 1.51 | 675000 | 1.6999 | |
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| 1.748 | 1.52 | 680000 | 1.6871 | |
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| 1.7476 | 1.53 | 685000 | 1.6884 | |
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| 1.7493 | 1.55 | 690000 | 1.6984 | |
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| 1.745 | 1.56 | 695000 | 1.6999 | |
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| 1.7397 | 1.57 | 700000 | 1.7036 | |
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| 1.7429 | 1.58 | 705000 | 1.7223 | |
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| 1.7367 | 1.59 | 710000 | 1.7111 | |
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| 1.7403 | 1.6 | 715000 | 1.6691 | |
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| 1.7361 | 1.61 | 720000 | 1.6693 | |
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| 1.737 | 1.62 | 725000 | 1.6884 | |
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| 1.7347 | 1.63 | 730000 | 1.6641 | |
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| 1.7323 | 1.65 | 735000 | 1.6628 | |
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| 1.7329 | 1.66 | 740000 | 1.6759 | |
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| 1.7292 | 1.67 | 745000 | 1.6654 | |
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| 1.7275 | 1.68 | 750000 | 1.6738 | |
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| 1.7266 | 1.69 | 755000 | 1.6792 | |
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| 1.7259 | 1.7 | 760000 | 1.6752 | |
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| 1.7231 | 1.71 | 765000 | 1.6641 | |
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| 1.7238 | 1.72 | 770000 | 1.6676 | |
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| 1.7223 | 1.74 | 775000 | 1.6563 | |
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| 1.722 | 1.75 | 780000 | 1.6541 | |
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| 1.7195 | 1.76 | 785000 | 1.6560 | |
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| 1.7171 | 1.77 | 790000 | 1.6786 | |
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| 1.7187 | 1.78 | 795000 | 1.6434 | |
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| 1.7186 | 1.79 | 800000 | 1.6538 | |
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| 1.7115 | 1.8 | 805000 | 1.6535 | |
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| 1.7119 | 1.81 | 810000 | 1.6738 | |
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| 1.7106 | 1.83 | 815000 | 1.6597 | |
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| 1.7088 | 1.84 | 820000 | 1.6486 | |
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| 1.7079 | 1.85 | 825000 | 1.6576 | |
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| 1.7062 | 1.86 | 830000 | 1.6676 | |
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| 1.7084 | 1.87 | 835000 | 1.6449 | |
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| 1.7059 | 1.88 | 840000 | 1.6515 | |
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| 1.7057 | 1.89 | 845000 | 1.6609 | |
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| 1.7021 | 1.9 | 850000 | 1.6482 | |
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| 1.7005 | 1.91 | 855000 | 1.6653 | |
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| 1.6988 | 1.93 | 860000 | 1.6801 | |
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| 1.6964 | 1.94 | 865000 | 1.6830 | |
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| 1.6954 | 1.95 | 870000 | 1.6589 | |
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| 1.693 | 1.96 | 875000 | 1.6553 | |
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| 1.689 | 1.97 | 880000 | 1.6554 | |
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| 1.69 | 1.98 | 885000 | 1.6424 | |
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| 1.6893 | 1.99 | 890000 | 1.6628 | |
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| 1.6772 | 2.0 | 895000 | 1.6709 | |
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| 1.6703 | 2.02 | 900000 | 1.6627 | |
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| 1.6726 | 2.03 | 905000 | 1.6612 | |
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| 1.669 | 2.04 | 910000 | 1.6595 | |
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| 1.6696 | 2.05 | 915000 | 1.6427 | |
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| 1.6672 | 2.06 | 920000 | 1.6497 | |
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| 1.669 | 2.07 | 925000 | 1.6288 | |
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| 1.6675 | 2.08 | 930000 | 1.6443 | |
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| 1.6685 | 2.09 | 935000 | 1.6316 | |
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| 1.6671 | 2.11 | 940000 | 1.6451 | |
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| 1.6673 | 2.12 | 945000 | 1.6313 | |
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| 1.6649 | 2.13 | 950000 | 1.6363 | |
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| 1.6655 | 2.14 | 955000 | 1.6440 | |
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| 1.6637 | 2.15 | 960000 | 1.6238 | |
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| 1.6632 | 2.16 | 965000 | 1.6226 | |
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| 1.6599 | 2.17 | 970000 | 1.6171 | |
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| 1.6602 | 2.18 | 975000 | 1.6466 | |
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| 1.658 | 2.19 | 980000 | 1.6341 | |
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| 1.6571 | 2.21 | 985000 | 1.6500 | |
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| 1.6572 | 2.22 | 990000 | 1.6225 | |
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| 1.6572 | 2.23 | 995000 | 1.6296 | |
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| 1.6552 | 2.24 | 1000000 | 1.6437 | |
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| 1.6548 | 2.25 | 1005000 | 1.6162 | |
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| 1.6552 | 2.26 | 1010000 | 1.6223 | |
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| 1.6544 | 2.27 | 1015000 | 1.6355 | |
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| 1.6464 | 2.28 | 1020000 | 1.6250 | |
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| 1.652 | 2.3 | 1025000 | 1.6217 | |
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| 1.6481 | 2.31 | 1030000 | 1.6079 | |
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| 1.6466 | 2.32 | 1035000 | 1.6110 | |
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| 1.6462 | 2.33 | 1040000 | 1.6210 | |
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| 1.6448 | 2.34 | 1045000 | 1.5993 | |
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| 1.6461 | 2.35 | 1050000 | 1.6096 | |
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| 1.6396 | 2.36 | 1055000 | 1.6137 | |
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| 1.644 | 2.37 | 1060000 | 1.6189 | |
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| 1.6396 | 2.39 | 1065000 | 1.6211 | |
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| 1.639 | 2.4 | 1070000 | 1.6149 | |
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| 1.6358 | 2.41 | 1075000 | 1.6144 | |
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| 1.6356 | 2.42 | 1080000 | 1.6018 | |
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| 1.6364 | 2.43 | 1085000 | 1.5999 | |
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| 1.6352 | 2.44 | 1090000 | 1.6095 | |
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| 1.634 | 2.45 | 1095000 | 1.6114 | |
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| 1.6279 | 2.46 | 1100000 | 1.6156 | |
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| 1.6272 | 2.47 | 1105000 | 1.6124 | |
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| 1.6319 | 2.49 | 1110000 | 1.6046 | |
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| 1.6276 | 2.5 | 1115000 | 1.6152 | |
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| 1.6285 | 2.51 | 1120000 | 1.6129 | |
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| 1.6242 | 2.52 | 1125000 | 1.5984 | |
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| 1.6261 | 2.53 | 1130000 | 1.6116 | |
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| 1.623 | 2.54 | 1135000 | 1.6061 | |
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| 1.6203 | 2.55 | 1140000 | 1.6182 | |
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| 1.62 | 2.56 | 1145000 | 1.5887 | |
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| 1.6177 | 2.58 | 1150000 | 1.5731 | |
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| 1.6172 | 2.59 | 1155000 | 1.5990 | |
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| 1.6179 | 2.6 | 1160000 | 1.5965 | |
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| 1.6206 | 2.61 | 1165000 | 1.6000 | |
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| 1.6156 | 2.62 | 1170000 | 1.5873 | |
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| 1.6124 | 2.63 | 1175000 | 1.5899 | |
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| 1.613 | 2.64 | 1180000 | 1.5910 | |
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| 1.6134 | 2.65 | 1185000 | 1.6017 | |
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| 1.609 | 2.67 | 1190000 | 1.5822 | |
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| 1.6084 | 2.68 | 1195000 | 1.5906 | |
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| 1.6101 | 2.69 | 1200000 | 1.6218 | |
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| 1.6077 | 2.7 | 1205000 | 1.6149 | |
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| 1.6057 | 2.71 | 1210000 | 1.5994 | |
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| 1.6018 | 2.72 | 1215000 | 1.5839 | |
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| 1.6049 | 2.73 | 1220000 | 1.5864 | |
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| 1.6012 | 2.74 | 1225000 | 1.5994 | |
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| 1.6013 | 2.75 | 1230000 | 1.5821 | |
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| 1.5957 | 2.77 | 1235000 | 1.5964 | |
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| 1.5971 | 2.78 | 1240000 | 1.5897 | |
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| 1.5967 | 2.79 | 1245000 | 1.5774 | |
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| 1.5927 | 2.8 | 1250000 | 1.5861 | |
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| 1.5954 | 2.81 | 1255000 | 1.5789 | |
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| 1.5937 | 2.82 | 1260000 | 1.5739 | |
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| 1.5895 | 2.83 | 1265000 | 1.5701 | |
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| 1.5912 | 2.84 | 1270000 | 1.5622 | |
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| 1.5922 | 2.86 | 1275000 | 1.5730 | |
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| 1.5883 | 2.87 | 1280000 | 1.5775 | |
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| 1.5864 | 2.88 | 1285000 | 1.5726 | |
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| 1.5837 | 2.89 | 1290000 | 1.5679 | |
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| 1.5824 | 2.9 | 1295000 | 1.5683 | |
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| 1.5817 | 2.91 | 1300000 | 1.5508 | |
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| 1.5778 | 2.92 | 1305000 | 1.5620 | |
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| 1.5822 | 2.93 | 1310000 | 1.5556 | |
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| 1.5783 | 2.95 | 1315000 | 1.5693 | |
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| 1.5751 | 2.96 | 1320000 | 1.5781 | |
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| 1.5716 | 2.97 | 1325000 | 1.5655 | |
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| 1.5765 | 2.98 | 1330000 | 1.5528 | |
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| 1.5728 | 2.99 | 1335000 | 1.5748 | |
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| 1.5672 | 3.0 | 1340000 | 1.5597 | |
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| 1.5467 | 3.01 | 1345000 | 1.5461 | |
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| 1.547 | 3.02 | 1350000 | 1.5516 | |
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| 1.5462 | 3.03 | 1355000 | 1.5519 | |
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| 1.5464 | 3.05 | 1360000 | 1.5593 | |
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| 1.5457 | 3.06 | 1365000 | 1.5576 | |
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| 1.5441 | 3.07 | 1370000 | 1.5653 | |
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| 1.544 | 3.08 | 1375000 | 1.5662 | |
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| 1.5467 | 3.09 | 1380000 | 1.5611 | |
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| 1.5439 | 3.1 | 1385000 | 1.5635 | |
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| 1.5449 | 3.11 | 1390000 | 1.5467 | |
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| 1.5417 | 3.12 | 1395000 | 1.5495 | |
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| 1.5428 | 3.14 | 1400000 | 1.5552 | |
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| 1.5432 | 3.15 | 1405000 | 1.5347 | |
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| 1.5401 | 3.16 | 1410000 | 1.5394 | |
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| 1.5391 | 3.17 | 1415000 | 1.5497 | |
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| 1.539 | 3.18 | 1420000 | 1.5431 | |
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| 1.5368 | 3.19 | 1425000 | 1.5479 | |
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| 1.5365 | 3.2 | 1430000 | 1.5513 | |
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| 1.5327 | 3.21 | 1435000 | 1.5467 | |
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| 1.5337 | 3.23 | 1440000 | 1.5477 | |
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| 1.5317 | 3.24 | 1445000 | 1.5398 | |
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| 1.5315 | 3.25 | 1450000 | 1.5481 | |
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| 1.532 | 3.26 | 1455000 | 1.5385 | |
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| 1.5312 | 3.27 | 1460000 | 1.5520 | |
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| 1.5328 | 3.28 | 1465000 | 1.5423 | |
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| 1.5288 | 3.29 | 1470000 | 1.5489 | |
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| 1.5271 | 3.3 | 1475000 | 1.5395 | |
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| 1.5273 | 3.31 | 1480000 | 1.5335 | |
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| 1.5235 | 3.33 | 1485000 | 1.5381 | |
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| 1.5224 | 3.34 | 1490000 | 1.5289 | |
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| 1.5206 | 3.35 | 1495000 | 1.5331 | |
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| 1.5189 | 3.36 | 1500000 | 1.5343 | |
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| 1.5152 | 3.37 | 1505000 | 1.5246 | |
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| 1.5225 | 3.38 | 1510000 | 1.5280 | |
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| 1.5168 | 3.39 | 1515000 | 1.5315 | |
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| 1.5161 | 3.4 | 1520000 | 1.5284 | |
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| 1.5111 | 3.42 | 1525000 | 1.5278 | |
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| 1.5154 | 3.43 | 1530000 | 1.5148 | |
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| 1.515 | 3.44 | 1535000 | 1.5286 | |
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| 1.5117 | 3.45 | 1540000 | 1.5291 | |
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| 1.5099 | 3.46 | 1545000 | 1.5320 | |
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| 1.5097 | 3.47 | 1550000 | 1.5323 | |
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| 1.5075 | 3.48 | 1555000 | 1.5157 | |
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| 1.5059 | 3.49 | 1560000 | 1.5214 | |
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| 1.5011 | 3.51 | 1565000 | 1.5199 | |
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| 1.5074 | 3.52 | 1570000 | 1.5114 | |
|
| 1.5033 | 3.53 | 1575000 | 1.5145 | |
|
| 1.5009 | 3.54 | 1580000 | 1.5184 | |
|
| 1.4994 | 3.55 | 1585000 | 1.5125 | |
|
| 1.5041 | 3.56 | 1590000 | 1.5048 | |
|
| 1.5002 | 3.57 | 1595000 | 1.5156 | |
|
| 1.4967 | 3.58 | 1600000 | 1.5176 | |
|
| 1.4923 | 3.59 | 1605000 | 1.5128 | |
|
| 1.495 | 3.61 | 1610000 | 1.5188 | |
|
| 1.4929 | 3.62 | 1615000 | 1.5149 | |
|
| 1.4921 | 3.63 | 1620000 | 1.5097 | |
|
| 1.4916 | 3.64 | 1625000 | 1.5161 | |
|
| 1.4852 | 3.65 | 1630000 | 1.5134 | |
|
| 1.4881 | 3.66 | 1635000 | 1.5101 | |
|
| 1.4873 | 3.67 | 1640000 | 1.5027 | |
|
| 1.4911 | 3.68 | 1645000 | 1.4968 | |
|
| 1.488 | 3.7 | 1650000 | 1.4962 | |
|
| 1.4842 | 3.71 | 1655000 | 1.5030 | |
|
| 1.4829 | 3.72 | 1660000 | 1.5041 | |
|
| 1.4816 | 3.73 | 1665000 | 1.5076 | |
|
| 1.479 | 3.74 | 1670000 | 1.5029 | |
|
| 1.4768 | 3.75 | 1675000 | 1.5053 | |
|
| 1.4769 | 3.76 | 1680000 | 1.5026 | |
|
| 1.4781 | 3.77 | 1685000 | 1.5016 | |
|
| 1.4781 | 3.79 | 1690000 | 1.5034 | |
|
| 1.4777 | 3.8 | 1695000 | 1.4976 | |
|
| 1.4736 | 3.81 | 1700000 | 1.5002 | |
|
| 1.4715 | 3.82 | 1705000 | 1.4995 | |
|
| 1.4716 | 3.83 | 1710000 | 1.4996 | |
|
| 1.4648 | 3.84 | 1715000 | 1.4952 | |
|
| 1.4711 | 3.85 | 1720000 | 1.4934 | |
|
| 1.4682 | 3.86 | 1725000 | 1.4965 | |
|
| 1.4659 | 3.87 | 1730000 | 1.4932 | |
|
| 1.4689 | 3.89 | 1735000 | 1.4920 | |
|
| 1.4656 | 3.9 | 1740000 | 1.4910 | |
|
| 1.4666 | 3.91 | 1745000 | 1.4893 | |
|
| 1.4611 | 3.92 | 1750000 | 1.4888 | |
|
| 1.4623 | 3.93 | 1755000 | 1.4898 | |
|
| 1.4637 | 3.94 | 1760000 | 1.4909 | |
|
| 1.4585 | 3.95 | 1765000 | 1.4858 | |
|
| 1.4586 | 3.96 | 1770000 | 1.4847 | |
|
| 1.4579 | 3.98 | 1775000 | 1.4841 | |
|
| 1.458 | 3.99 | 1780000 | 1.4840 | |
|
| 1.4572 | 4.0 | 1785000 | 1.4832 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.19.2 |
|
- Pytorch 1.11.0+cu113 |
|
- Datasets 2.2.2 |
|
- Tokenizers 0.12.1 |
|
|
