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PeptideGPT_non_hemolytic

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Safetensors
gpt2
Generated from Trainer
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Uploaded PeptideGPT non-hemolytic model

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  1. README.md +559 -0
  2. all_results.json +15 -0
  3. config.json +39 -0
  4. eval_results.json +10 -0
  5. events.out.tfevents.1711986222.lambda-a6000.2759502.0 +3 -0
  6. generation_config.json +6 -0
  7. merges.txt +0 -0
  8. model.safetensors +3 -0
  9. special_tokens_map.json +23 -0
  10. tokenizer.json +0 -0
  11. tokenizer_config.json +19 -0
  12. train_results.json +8 -0
  13. trainer_state.json +0 -0
  14. training_args.bin +3 -0
  15. vocab.json +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: nferruz/ProtGPT2
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: output_hemo_neg_3
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+ results: []
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+ ---
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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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+
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+ # output_hemo_neg_3
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+
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+ This model is a fine-tuned version of [nferruz/ProtGPT2](https://huggingface.co/nferruz/ProtGPT2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.9794
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+ - Accuracy: 0.4240
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-06
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+ - train_batch_size: 1
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+ - eval_batch_size: 8
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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: 500.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 5.9415 | 1.0 | 38 | 5.6068 | 0.3084 |
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+ | 5.7302 | 2.0 | 76 | 5.4263 | 0.3204 |
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+ | 5.5675 | 3.0 | 114 | 5.2875 | 0.3231 |
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+ | 5.4594 | 4.0 | 152 | 5.2055 | 0.3250 |
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+ | 5.3808 | 5.0 | 190 | 5.1589 | 0.3297 |
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+ | 5.3353 | 6.0 | 228 | 5.1195 | 0.3321 |
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+ | 5.2946 | 7.0 | 266 | 5.0779 | 0.3338 |
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+ | 5.2632 | 8.0 | 304 | 5.0432 | 0.3370 |
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+ | 5.2279 | 9.0 | 342 | 5.0154 | 0.3372 |
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+ | 5.1999 | 10.0 | 380 | 4.9931 | 0.3377 |
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+ | 5.1853 | 11.0 | 418 | 4.9701 | 0.3399 |
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+ | 5.1619 | 12.0 | 456 | 4.9458 | 0.3429 |
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+ | 5.1395 | 13.0 | 494 | 4.9274 | 0.3438 |
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+ | 5.1179 | 14.0 | 532 | 4.9080 | 0.3463 |
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+ | 5.1048 | 15.0 | 570 | 4.8921 | 0.3465 |
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+ | 5.0837 | 16.0 | 608 | 4.8756 | 0.3470 |
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+ | 5.067 | 17.0 | 646 | 4.8606 | 0.3492 |
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+ | 5.0516 | 18.0 | 684 | 4.8469 | 0.3507 |
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+ | 5.0313 | 19.0 | 722 | 4.8366 | 0.3522 |
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+ | 5.0225 | 20.0 | 760 | 4.8276 | 0.3526 |
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+ | 5.0068 | 21.0 | 798 | 4.8179 | 0.3522 |
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+ | 4.9942 | 22.0 | 836 | 4.8051 | 0.3522 |
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+ | 4.9758 | 23.0 | 874 | 4.7963 | 0.3526 |
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+ | 4.9605 | 24.0 | 912 | 4.7843 | 0.3529 |
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+ | 4.9525 | 25.0 | 950 | 4.7728 | 0.3531 |
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+ | 4.9409 | 26.0 | 988 | 4.7618 | 0.3524 |
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+ | 4.9328 | 27.0 | 1026 | 4.7523 | 0.3519 |
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+ | 4.9168 | 28.0 | 1064 | 4.7444 | 0.3526 |
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+ | 4.9057 | 29.0 | 1102 | 4.7332 | 0.3551 |
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+ | 4.8896 | 30.0 | 1140 | 4.7237 | 0.3561 |
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+ | 4.8869 | 31.0 | 1178 | 4.7156 | 0.3565 |
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+ | 4.8798 | 32.0 | 1216 | 4.7093 | 0.3568 |
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+ | 4.8591 | 33.0 | 1254 | 4.7029 | 0.3575 |
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+ | 4.8548 | 34.0 | 1292 | 4.6946 | 0.3570 |
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+ | 4.8502 | 35.0 | 1330 | 4.6871 | 0.3595 |
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+ | 4.8378 | 36.0 | 1368 | 4.6803 | 0.3595 |
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+ | 4.829 | 37.0 | 1406 | 4.6733 | 0.3600 |
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+ | 4.8177 | 38.0 | 1444 | 4.6643 | 0.3602 |
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+ | 4.809 | 39.0 | 1482 | 4.6591 | 0.3607 |
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+ | 4.8002 | 40.0 | 1520 | 4.6507 | 0.3607 |
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+ | 4.7938 | 41.0 | 1558 | 4.6438 | 0.3614 |
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+ | 4.7787 | 42.0 | 1596 | 4.6367 | 0.3617 |
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+ | 4.7685 | 43.0 | 1634 | 4.6306 | 0.3629 |
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+ | 4.762 | 44.0 | 1672 | 4.6211 | 0.3636 |
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+ | 4.7487 | 45.0 | 1710 | 4.6133 | 0.3641 |
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+ | 4.7451 | 46.0 | 1748 | 4.6058 | 0.3646 |
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+ | 4.7378 | 47.0 | 1786 | 4.6009 | 0.3658 |
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+ | 4.7281 | 48.0 | 1824 | 4.5932 | 0.3658 |
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+ | 4.7196 | 49.0 | 1862 | 4.5889 | 0.3656 |
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+ | 4.7091 | 50.0 | 1900 | 4.5814 | 0.3666 |
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+ | 4.7032 | 51.0 | 1938 | 4.5763 | 0.3668 |
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+ | 4.6978 | 52.0 | 1976 | 4.5731 | 0.3668 |
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+ | 4.6908 | 53.0 | 2014 | 4.5682 | 0.3673 |
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+ | 4.6776 | 54.0 | 2052 | 4.5638 | 0.3673 |
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+ | 4.6667 | 55.0 | 2090 | 4.5588 | 0.3680 |
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+ | 4.6662 | 56.0 | 2128 | 4.5535 | 0.3685 |
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+ | 4.6567 | 57.0 | 2166 | 4.5494 | 0.3697 |
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+ | 4.6492 | 58.0 | 2204 | 4.5433 | 0.3697 |
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+ | 4.6442 | 59.0 | 2242 | 4.5421 | 0.3697 |
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+ | 4.632 | 60.0 | 2280 | 4.5368 | 0.3700 |
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+ | 4.6256 | 61.0 | 2318 | 4.5321 | 0.3705 |
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+ | 4.6215 | 62.0 | 2356 | 4.5286 | 0.3700 |
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+ | 4.6142 | 63.0 | 2394 | 4.5240 | 0.3702 |
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+ | 4.6041 | 64.0 | 2432 | 4.5195 | 0.3710 |
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+ | 4.5984 | 65.0 | 2470 | 4.5147 | 0.3715 |
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+ | 4.5919 | 66.0 | 2508 | 4.5116 | 0.3727 |
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+ | 4.5838 | 67.0 | 2546 | 4.5070 | 0.3724 |
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+ | 4.5733 | 68.0 | 2584 | 4.5035 | 0.3724 |
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+ | 4.5642 | 69.0 | 2622 | 4.5007 | 0.3722 |
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+ | 4.5607 | 70.0 | 2660 | 4.4968 | 0.3719 |
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+ | 4.5543 | 71.0 | 2698 | 4.4928 | 0.3729 |
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+ | 4.5502 | 72.0 | 2736 | 4.4897 | 0.3729 |
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+ | 4.5505 | 73.0 | 2774 | 4.4875 | 0.3737 |
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+ | 4.537 | 74.0 | 2812 | 4.4840 | 0.3732 |
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+ | 4.5087 | 78.0 | 2964 | 4.4716 | 0.3751 |
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+ | 4.504 | 79.0 | 3002 | 4.4684 | 0.3744 |
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+ | 4.4914 | 80.0 | 3040 | 4.4634 | 0.3751 |
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+ | 4.4907 | 81.0 | 3078 | 4.4616 | 0.3751 |
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+ | 4.483 | 82.0 | 3116 | 4.4578 | 0.3754 |
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+ | 4.4792 | 83.0 | 3154 | 4.4541 | 0.3741 |
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+ | 4.4705 | 84.0 | 3192 | 4.4511 | 0.3744 |
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+ | 4.4647 | 85.0 | 3230 | 4.4488 | 0.3749 |
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+ | 4.4617 | 86.0 | 3268 | 4.4445 | 0.3751 |
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+ | 4.453 | 87.0 | 3306 | 4.4385 | 0.3751 |
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+ | 4.4488 | 88.0 | 3344 | 4.4353 | 0.3763 |
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+ | 4.4424 | 89.0 | 3382 | 4.4322 | 0.3766 |
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+ | 4.433 | 90.0 | 3420 | 4.4300 | 0.3766 |
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+ | 4.4252 | 91.0 | 3458 | 4.4259 | 0.3763 |
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+ | 4.4226 | 92.0 | 3496 | 4.4215 | 0.3773 |
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+ | 4.4144 | 93.0 | 3534 | 4.4189 | 0.3771 |
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+ | 4.4047 | 94.0 | 3572 | 4.4160 | 0.3771 |
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+ | 4.4071 | 95.0 | 3610 | 4.4131 | 0.3773 |
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+ | 4.3975 | 96.0 | 3648 | 4.4095 | 0.3773 |
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+ | 4.3897 | 97.0 | 3686 | 4.4085 | 0.3771 |
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+ | 4.3869 | 98.0 | 3724 | 4.4052 | 0.3771 |
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+ | 4.3751 | 99.0 | 3762 | 4.4021 | 0.3773 |
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+ | 4.3698 | 100.0 | 3800 | 4.3988 | 0.3768 |
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+ | 4.368 | 101.0 | 3838 | 4.3945 | 0.3768 |
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+ | 4.3643 | 102.0 | 3876 | 4.3918 | 0.3771 |
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+ | 4.3552 | 103.0 | 3914 | 4.3893 | 0.3766 |
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+ | 4.3478 | 104.0 | 3952 | 4.3869 | 0.3776 |
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+ | 4.3438 | 105.0 | 3990 | 4.3848 | 0.3781 |
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+ | 4.3362 | 106.0 | 4028 | 4.3820 | 0.3773 |
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+ | 4.3356 | 107.0 | 4066 | 4.3768 | 0.3778 |
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+ | 4.3263 | 108.0 | 4104 | 4.3764 | 0.3776 |
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+ | 4.3238 | 109.0 | 4142 | 4.3732 | 0.3778 |
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+ | 4.3157 | 110.0 | 4180 | 4.3699 | 0.3781 |
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+ | 4.311 | 111.0 | 4218 | 4.3678 | 0.3781 |
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+ | 4.3048 | 112.0 | 4256 | 4.3646 | 0.3788 |
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+ | 4.2955 | 113.0 | 4294 | 4.3640 | 0.3793 |
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+ | 4.2914 | 114.0 | 4332 | 4.3604 | 0.3793 |
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+ | 4.286 | 115.0 | 4370 | 4.3580 | 0.3790 |
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+ | 4.2857 | 116.0 | 4408 | 4.3541 | 0.3790 |
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+ | 4.2776 | 117.0 | 4446 | 4.3527 | 0.3793 |
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+ | 4.2734 | 118.0 | 4484 | 4.3482 | 0.3803 |
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+ | 4.2646 | 119.0 | 4522 | 4.3461 | 0.3800 |
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+ | 4.2632 | 120.0 | 4560 | 4.3446 | 0.3803 |
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+ | 4.2586 | 121.0 | 4598 | 4.3409 | 0.3807 |
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+ | 4.2564 | 122.0 | 4636 | 4.3400 | 0.3812 |
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+ | 4.2423 | 123.0 | 4674 | 4.3357 | 0.3807 |
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+ | 4.2425 | 124.0 | 4712 | 4.3335 | 0.3807 |
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+ | 4.2367 | 125.0 | 4750 | 4.3306 | 0.3810 |
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+ | 4.2301 | 126.0 | 4788 | 4.3292 | 0.3815 |
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+ | 4.2286 | 127.0 | 4826 | 4.3276 | 0.3812 |
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+ | 4.2184 | 128.0 | 4864 | 4.3246 | 0.3822 |
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+ | 4.2156 | 129.0 | 4902 | 4.3210 | 0.3827 |
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+ | 4.2116 | 130.0 | 4940 | 4.3187 | 0.3834 |
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+ | 4.2008 | 131.0 | 4978 | 4.3165 | 0.3834 |
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+ | 4.1995 | 132.0 | 5016 | 4.3134 | 0.3834 |
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+ | 4.19 | 133.0 | 5054 | 4.3136 | 0.3842 |
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+ | 4.1828 | 134.0 | 5092 | 4.3116 | 0.3842 |
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+ | 4.1815 | 135.0 | 5130 | 4.3065 | 0.3847 |
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+ | 4.1771 | 136.0 | 5168 | 4.3051 | 0.3839 |
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+ | 4.1744 | 137.0 | 5206 | 4.3016 | 0.3847 |
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+ | 4.1717 | 138.0 | 5244 | 4.2975 | 0.3847 |
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+ | 4.1616 | 139.0 | 5282 | 4.2966 | 0.3847 |
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+ | 4.1582 | 140.0 | 5320 | 4.2948 | 0.3847 |
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+ | 4.1583 | 141.0 | 5358 | 4.2931 | 0.3849 |
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+ | 4.148 | 142.0 | 5396 | 4.2894 | 0.3854 |
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+ | 4.1417 | 143.0 | 5434 | 4.2861 | 0.3849 |
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+ | 4.1386 | 144.0 | 5472 | 4.2865 | 0.3861 |
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+ | 4.133 | 145.0 | 5510 | 4.2834 | 0.3861 |
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+ | 4.129 | 146.0 | 5548 | 4.2793 | 0.3864 |
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+ | 4.12 | 147.0 | 5586 | 4.2785 | 0.3861 |
199
+ | 4.1206 | 148.0 | 5624 | 4.2750 | 0.3864 |
200
+ | 4.1226 | 149.0 | 5662 | 4.2744 | 0.3871 |
201
+ | 4.1104 | 150.0 | 5700 | 4.2723 | 0.3866 |
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+ | 4.1093 | 151.0 | 5738 | 4.2677 | 0.3871 |
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+ | 4.0989 | 152.0 | 5776 | 4.2654 | 0.3869 |
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+ | 4.1035 | 153.0 | 5814 | 4.2646 | 0.3878 |
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+ | 4.0949 | 154.0 | 5852 | 4.2635 | 0.3881 |
206
+ | 4.0921 | 155.0 | 5890 | 4.2606 | 0.3883 |
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+ | 4.0883 | 156.0 | 5928 | 4.2565 | 0.3886 |
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+ | 4.0794 | 157.0 | 5966 | 4.2558 | 0.3893 |
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+ | 4.0754 | 158.0 | 6004 | 4.2530 | 0.3888 |
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+ | 4.0756 | 159.0 | 6042 | 4.2496 | 0.3893 |
211
+ | 4.067 | 160.0 | 6080 | 4.2501 | 0.3888 |
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+ | 4.0627 | 161.0 | 6118 | 4.2484 | 0.3891 |
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+ | 4.0586 | 162.0 | 6156 | 4.2439 | 0.3898 |
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+ | 4.0577 | 163.0 | 6194 | 4.2431 | 0.3893 |
215
+ | 4.055 | 164.0 | 6232 | 4.2391 | 0.3895 |
216
+ | 4.0419 | 165.0 | 6270 | 4.2396 | 0.3895 |
217
+ | 4.0411 | 166.0 | 6308 | 4.2365 | 0.3903 |
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+ | 4.0405 | 167.0 | 6346 | 4.2356 | 0.3908 |
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+ | 4.0327 | 168.0 | 6384 | 4.2349 | 0.3905 |
220
+ | 4.0262 | 169.0 | 6422 | 4.2312 | 0.3913 |
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+ | 4.0252 | 170.0 | 6460 | 4.2300 | 0.3913 |
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+ | 4.0237 | 171.0 | 6498 | 4.2254 | 0.3915 |
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+ | 4.024 | 172.0 | 6536 | 4.2248 | 0.3920 |
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+ | 4.0137 | 173.0 | 6574 | 4.2218 | 0.3922 |
225
+ | 4.0108 | 174.0 | 6612 | 4.2224 | 0.3927 |
226
+ | 4.0037 | 175.0 | 6650 | 4.2190 | 0.3939 |
227
+ | 4.0021 | 176.0 | 6688 | 4.2180 | 0.3937 |
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+ | 3.9949 | 177.0 | 6726 | 4.2150 | 0.3942 |
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+ | 3.9957 | 178.0 | 6764 | 4.2135 | 0.3939 |
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+ | 3.9923 | 179.0 | 6802 | 4.2094 | 0.3942 |
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+ | 3.9853 | 180.0 | 6840 | 4.2092 | 0.3949 |
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+ | 3.9779 | 181.0 | 6878 | 4.2086 | 0.3949 |
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+ | 3.9826 | 182.0 | 6916 | 4.2045 | 0.3947 |
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+ | 3.9775 | 183.0 | 6954 | 4.2012 | 0.3949 |
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+ | 3.9706 | 184.0 | 6992 | 4.2005 | 0.3961 |
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+ | 3.9672 | 185.0 | 7030 | 4.1992 | 0.3957 |
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+ | 3.9707 | 186.0 | 7068 | 4.1964 | 0.3966 |
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+ | 3.9585 | 187.0 | 7106 | 4.1951 | 0.3971 |
239
+ | 3.9552 | 188.0 | 7144 | 4.1927 | 0.3966 |
240
+ | 3.9526 | 189.0 | 7182 | 4.1922 | 0.3966 |
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+ | 3.9514 | 190.0 | 7220 | 4.1886 | 0.3969 |
242
+ | 3.9464 | 191.0 | 7258 | 4.1886 | 0.3976 |
243
+ | 3.9433 | 192.0 | 7296 | 4.1856 | 0.3981 |
244
+ | 3.9378 | 193.0 | 7334 | 4.1846 | 0.3978 |
245
+ | 3.9362 | 194.0 | 7372 | 4.1831 | 0.3981 |
246
+ | 3.9307 | 195.0 | 7410 | 4.1820 | 0.3981 |
247
+ | 3.9324 | 196.0 | 7448 | 4.1767 | 0.3978 |
248
+ | 3.9223 | 197.0 | 7486 | 4.1794 | 0.3983 |
249
+ | 3.9279 | 198.0 | 7524 | 4.1752 | 0.3986 |
250
+ | 3.9214 | 199.0 | 7562 | 4.1727 | 0.3981 |
251
+ | 3.9122 | 200.0 | 7600 | 4.1746 | 0.3988 |
252
+ | 3.9099 | 201.0 | 7638 | 4.1698 | 0.3996 |
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+ | 3.9075 | 202.0 | 7676 | 4.1692 | 0.3993 |
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+ | 3.9095 | 203.0 | 7714 | 4.1661 | 0.4000 |
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+ | 3.9 | 204.0 | 7752 | 4.1637 | 0.4008 |
256
+ | 3.9004 | 205.0 | 7790 | 4.1619 | 0.4003 |
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+ | 3.8978 | 206.0 | 7828 | 4.1603 | 0.4005 |
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+ | 3.8918 | 207.0 | 7866 | 4.1583 | 0.4005 |
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+ | 3.8848 | 208.0 | 7904 | 4.1580 | 0.4008 |
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+ | 3.8831 | 209.0 | 7942 | 4.1577 | 0.4000 |
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+ | 3.8821 | 210.0 | 7980 | 4.1550 | 0.4005 |
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+ | 3.8818 | 211.0 | 8018 | 4.1522 | 0.4008 |
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+ | 3.8764 | 212.0 | 8056 | 4.1521 | 0.4008 |
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+ | 3.8704 | 213.0 | 8094 | 4.1491 | 0.4010 |
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+ | 3.8725 | 214.0 | 8132 | 4.1492 | 0.4010 |
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+ | 3.8698 | 215.0 | 8170 | 4.1470 | 0.4010 |
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+ | 3.8654 | 216.0 | 8208 | 4.1465 | 0.4018 |
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+ | 3.8608 | 217.0 | 8246 | 4.1451 | 0.4020 |
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+ | 3.8584 | 218.0 | 8284 | 4.1422 | 0.4015 |
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+ | 3.8546 | 219.0 | 8322 | 4.1412 | 0.4025 |
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+ | 3.8494 | 220.0 | 8360 | 4.1408 | 0.4022 |
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+ | 3.8479 | 221.0 | 8398 | 4.1384 | 0.4025 |
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+ | 3.8463 | 222.0 | 8436 | 4.1365 | 0.4025 |
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+ | 3.8422 | 223.0 | 8474 | 4.1326 | 0.4030 |
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+ | 3.8395 | 224.0 | 8512 | 4.1333 | 0.4022 |
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+ | 3.8369 | 225.0 | 8550 | 4.1338 | 0.4035 |
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+ | 3.8357 | 226.0 | 8588 | 4.1299 | 0.4047 |
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+ | 3.8318 | 227.0 | 8626 | 4.1298 | 0.4042 |
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+ | 3.8258 | 228.0 | 8664 | 4.1298 | 0.4040 |
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+ | 3.8265 | 229.0 | 8702 | 4.1276 | 0.4044 |
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+ | 3.8229 | 230.0 | 8740 | 4.1266 | 0.4042 |
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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300
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301
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302
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303
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304
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305
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306
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307
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308
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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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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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361
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362
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363
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364
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365
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366
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367
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368
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369
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370
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371
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372
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373
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375
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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390
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391
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392
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393
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395
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396
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397
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398
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399
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400
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401
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402
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403
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404
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405
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406
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407
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408
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409
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410
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411
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412
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413
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414
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415
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416
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417
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418
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419
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420
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421
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422
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423
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424
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425
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426
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427
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428
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429
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430
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431
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432
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433
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434
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435
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436
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441
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443
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445
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447
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448
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449
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450
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451
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453
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455
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456
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457
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458
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459
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460
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461
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462
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463
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464
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465
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466
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467
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468
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469
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470
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471
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472
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473
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474
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475
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476
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477
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478
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479
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480
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481
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482
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483
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484
+ | 3.5009 | 433.0 | 16454 | 3.9849 | 0.4225 |
485
+ | 3.5023 | 434.0 | 16492 | 3.9856 | 0.4228 |
486
+ | 3.4982 | 435.0 | 16530 | 3.9860 | 0.4228 |
487
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488
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489
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490
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491
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492
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493
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494
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495
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496
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497
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498
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499
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500
+ | 3.4936 | 449.0 | 17062 | 3.9847 | 0.4233 |
501
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502
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503
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504
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505
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506
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507
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508
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509
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510
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511
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512
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513
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514
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515
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516
+ | 3.4851 | 465.0 | 17670 | 3.9810 | 0.4235 |
517
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518
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519
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520
+ | 3.4791 | 469.0 | 17822 | 3.9815 | 0.4238 |
521
+ | 3.4814 | 470.0 | 17860 | 3.9813 | 0.4238 |
522
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523
+ | 3.4861 | 472.0 | 17936 | 3.9806 | 0.4235 |
524
+ | 3.4825 | 473.0 | 17974 | 3.9809 | 0.4235 |
525
+ | 3.4758 | 474.0 | 18012 | 3.9811 | 0.4235 |
526
+ | 3.4811 | 475.0 | 18050 | 3.9807 | 0.4235 |
527
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528
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529
+ | 3.4843 | 478.0 | 18164 | 3.9803 | 0.4240 |
530
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531
+ | 3.4807 | 480.0 | 18240 | 3.9800 | 0.4240 |
532
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533
+ | 3.4805 | 482.0 | 18316 | 3.9797 | 0.4240 |
534
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535
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536
+ | 3.4802 | 485.0 | 18430 | 3.9794 | 0.4240 |
537
+ | 3.4805 | 486.0 | 18468 | 3.9796 | 0.4240 |
538
+ | 3.4831 | 487.0 | 18506 | 3.9796 | 0.4240 |
539
+ | 3.4846 | 488.0 | 18544 | 3.9798 | 0.4240 |
540
+ | 3.4824 | 489.0 | 18582 | 3.9798 | 0.4240 |
541
+ | 3.4807 | 490.0 | 18620 | 3.9799 | 0.4240 |
542
+ | 3.4809 | 491.0 | 18658 | 3.9799 | 0.4240 |
543
+ | 3.4801 | 492.0 | 18696 | 3.9799 | 0.4238 |
544
+ | 3.479 | 493.0 | 18734 | 3.9799 | 0.4238 |
545
+ | 3.48 | 494.0 | 18772 | 3.9799 | 0.4238 |
546
+ | 3.4828 | 495.0 | 18810 | 3.9799 | 0.4238 |
547
+ | 3.4812 | 496.0 | 18848 | 3.9799 | 0.4238 |
548
+ | 3.4798 | 497.0 | 18886 | 3.9799 | 0.4238 |
549
+ | 3.4866 | 498.0 | 18924 | 3.9799 | 0.4238 |
550
+ | 3.4785 | 499.0 | 18962 | 3.9799 | 0.4238 |
551
+ | 3.4893 | 500.0 | 19000 | 3.9799 | 0.4238 |
552
+
553
+
554
+ ### Framework versions
555
+
556
+ - Transformers 4.38.0.dev0
557
+ - Pytorch 2.2.0
558
+ - Datasets 2.16.1
559
+ - Tokenizers 0.15.1
all_results.json ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 500.0,
3
+ "eval_accuracy": 0.4239980449657869,
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+ "eval_loss": 3.9793689250946045,
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+ "eval_runtime": 0.6297,
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+ "eval_samples": 4,
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+ "eval_samples_per_second": 6.352,
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+ "eval_steps_per_second": 1.588,
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+ "perplexity": 53.4832716246652,
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+ "train_loss": 3.948820646587171,
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+ "train_runtime": 16522.6397,
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+ "train_samples": 38,
13
+ "train_samples_per_second": 1.15,
14
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