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ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
gary109/AI_Light_Dance
generated_from_trainer
Inference Endpoints
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update model card README.md

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  ---
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  tags:
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- - automatic-speech-recognition
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- - gary109/AI_Light_Dance
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  - generated_from_trainer
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  model-index:
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  - name: ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53
@@ -13,10 +11,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53
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- This model is a fine-tuned version of [gary109/ai-light-dance_pretrain2_wav2vec2-large-xlsr-53](https://huggingface.co/gary109/ai-light-dance_pretrain2_wav2vec2-large-xlsr-53) on the GARY109/AI_LIGHT_DANCE - ONSET-SINGING3 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.5726
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- - Wer: 0.9965
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  ## Model description
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@@ -51,106 +49,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 2.1979 | 1.0 | 72 | 3.4874 | 0.9922 |
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- | 1.9612 | 2.0 | 144 | 4.5105 | 0.9889 |
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- | 1.8052 | 3.0 | 216 | 4.0819 | 0.9787 |
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- | 1.827 | 4.0 | 288 | 4.4058 | 0.9844 |
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- | 1.6249 | 5.0 | 360 | 4.8895 | 0.9872 |
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- | 1.6285 | 6.0 | 432 | 4.7534 | 0.9837 |
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- | 1.6713 | 7.0 | 504 | 4.5588 | 0.9819 |
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- | 1.777 | 8.0 | 576 | 4.7414 | 0.9860 |
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- | 1.6759 | 9.0 | 648 | 4.5222 | 0.9874 |
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- | 1.5533 | 10.0 | 720 | 3.6153 | 0.9824 |
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- | 1.5053 | 11.0 | 792 | 5.6485 | 0.9907 |
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- | 1.6541 | 12.0 | 864 | 5.4657 | 0.9843 |
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- | 1.5891 | 13.0 | 936 | 4.4534 | 0.9877 |
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- | 1.6809 | 14.0 | 1008 | 4.8404 | 0.9891 |
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- | 1.5506 | 15.0 | 1080 | 3.7248 | 0.9873 |
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- | 1.4754 | 16.0 | 1152 | 4.3970 | 0.9864 |
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- | 1.4576 | 17.0 | 1224 | 4.4771 | 0.9855 |
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- | 1.5614 | 18.0 | 1296 | 3.5102 | 0.9861 |
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- | 1.655 | 19.0 | 1368 | 4.8062 | 0.9863 |
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- | 1.455 | 20.0 | 1440 | 5.0790 | 0.9880 |
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- | 1.4701 | 21.0 | 1512 | 4.2320 | 0.9850 |
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- | 1.495 | 22.0 | 1584 | 5.2132 | 0.9889 |
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- | 1.5676 | 23.0 | 1656 | 4.1597 | 0.9806 |
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- | 1.5837 | 24.0 | 1728 | 5.0981 | 0.9867 |
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- | 1.4437 | 25.0 | 1800 | 3.6791 | 0.9813 |
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- | 1.4684 | 26.0 | 1872 | 4.0667 | 0.9869 |
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- | 1.4617 | 27.0 | 1944 | 5.2262 | 0.9902 |
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- | 1.5259 | 28.0 | 2016 | 4.5763 | 0.9876 |
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- | 1.5127 | 29.0 | 2088 | 3.5297 | 0.9831 |
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- | 1.4726 | 30.0 | 2160 | 3.2379 | 0.9776 |
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- | 1.446 | 31.0 | 2232 | 3.9459 | 0.9835 |
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- | 1.4116 | 32.0 | 2304 | 3.5352 | 0.9815 |
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- | 1.462 | 33.0 | 2376 | 3.3658 | 0.9761 |
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- | 1.498 | 34.0 | 2448 | 3.8620 | 0.9795 |
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- | 1.382 | 35.0 | 2520 | 3.4734 | 0.9798 |
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- | 1.3969 | 36.0 | 2592 | 3.7285 | 0.9780 |
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- | 1.3945 | 37.0 | 2664 | 3.7255 | 0.9820 |
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- | 1.4616 | 38.0 | 2736 | 3.8788 | 0.9812 |
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- | 1.4791 | 39.0 | 2808 | 3.1891 | 0.9781 |
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- | 1.3875 | 40.0 | 2880 | 3.6854 | 0.9801 |
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- | 1.3914 | 41.0 | 2952 | 3.4011 | 0.9742 |
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- | 1.3744 | 42.0 | 3024 | 3.5792 | 0.9808 |
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- | 1.4085 | 43.0 | 3096 | 2.9806 | 0.9743 |
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- | 1.407 | 44.0 | 3168 | 3.3188 | 0.9821 |
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- | 1.3678 | 45.0 | 3240 | 3.6300 | 0.9817 |
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- | 1.3762 | 46.0 | 3312 | 3.0986 | 0.9774 |
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- | 1.3507 | 47.0 | 3384 | 2.8956 | 0.9733 |
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- | 1.3646 | 48.0 | 3456 | 2.8360 | 0.9731 |
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- | 1.4027 | 49.0 | 3528 | 3.5181 | 0.9744 |
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- | 1.3383 | 50.0 | 3600 | 3.2710 | 0.9769 |
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- | 1.3517 | 51.0 | 3672 | 2.9974 | 0.9756 |
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- | 1.3551 | 52.0 | 3744 | 3.3180 | 0.9751 |
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- | 1.3493 | 53.0 | 3816 | 2.6087 | 0.9994 |
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- | 1.3977 | 54.0 | 3888 | 2.6875 | 0.9778 |
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- | 1.3254 | 55.0 | 3960 | 3.3663 | 0.9787 |
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- | 1.303 | 56.0 | 4032 | 2.6154 | 0.9692 |
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- | 1.2612 | 57.0 | 4104 | 3.2773 | 0.9761 |
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- | 1.3161 | 58.0 | 4176 | 2.9020 | 0.9717 |
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- | 1.3026 | 59.0 | 4248 | 3.1517 | 0.9709 |
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- | 1.262 | 60.0 | 4320 | 3.1299 | 0.9675 |
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- | 1.2885 | 61.0 | 4392 | 3.1023 | 0.9724 |
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- | 1.2538 | 62.0 | 4464 | 2.7857 | 0.9877 |
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- | 1.2536 | 63.0 | 4536 | 3.0150 | 0.9704 |
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- | 1.3339 | 64.0 | 4608 | 2.9305 | 0.9722 |
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- | 1.2392 | 65.0 | 4680 | 2.7695 | 0.9749 |
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- | 1.2572 | 66.0 | 4752 | 2.8677 | 0.9689 |
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- | 1.2538 | 67.0 | 4824 | 2.8597 | 0.9805 |
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- | 1.2355 | 68.0 | 4896 | 2.8300 | 0.9788 |
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- | 1.2682 | 69.0 | 4968 | 2.7011 | 0.9742 |
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- | 1.2252 | 70.0 | 5040 | 2.8322 | 0.9722 |
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- | 1.2085 | 71.0 | 5112 | 2.7401 | 0.9711 |
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- | 1.2412 | 72.0 | 5184 | 2.6227 | 0.9763 |
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- | 1.2148 | 73.0 | 5256 | 2.7146 | 0.9690 |
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- | 1.2411 | 74.0 | 5328 | 2.9963 | 0.9663 |
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- | 1.2012 | 75.0 | 5400 | 2.7940 | 0.9655 |
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- | 1.1969 | 76.0 | 5472 | 2.6212 | 0.9790 |
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- | 1.2004 | 77.0 | 5544 | 2.8644 | 0.9711 |
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- | 1.2247 | 78.0 | 5616 | 2.6127 | 0.9621 |
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- | 1.2791 | 79.0 | 5688 | 2.6538 | 0.9719 |
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- | 1.1867 | 80.0 | 5760 | 2.7779 | 0.9587 |
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- | 1.1992 | 81.0 | 5832 | 2.8297 | 0.9643 |
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- | 1.1833 | 82.0 | 5904 | 2.8508 | 0.9723 |
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- | 1.2092 | 83.0 | 5976 | 2.8261 | 0.9690 |
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- | 1.2215 | 84.0 | 6048 | 2.5995 | 0.9717 |
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- | 1.1966 | 85.0 | 6120 | 2.7659 | 0.9677 |
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- | 1.1774 | 86.0 | 6192 | 2.6289 | 0.9703 |
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- | 1.2002 | 87.0 | 6264 | 2.7197 | 0.9775 |
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- | 1.2035 | 88.0 | 6336 | 2.6154 | 0.9778 |
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- | 1.2219 | 89.0 | 6408 | 2.6426 | 0.9761 |
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- | 1.1724 | 90.0 | 6480 | 2.5996 | 0.9801 |
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- | 1.1832 | 91.0 | 6552 | 2.7315 | 0.9743 |
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- | 1.1759 | 92.0 | 6624 | 2.5726 | 0.9965 |
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- | 1.1638 | 93.0 | 6696 | 2.6570 | 0.9865 |
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- | 1.1872 | 94.0 | 6768 | 2.6414 | 0.9948 |
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- | 1.144 | 95.0 | 6840 | 2.6264 | 0.9863 |
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- | 1.1636 | 96.0 | 6912 | 2.5820 | 0.9918 |
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- | 1.1714 | 97.0 | 6984 | 2.5970 | 0.9913 |
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- | 1.1943 | 98.0 | 7056 | 2.6308 | 0.9895 |
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- | 1.185 | 99.0 | 7128 | 2.6379 | 0.9898 |
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- | 1.1569 | 100.0 | 7200 | 2.6331 | 0.9906 |
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  ### Framework versions
1
  ---
2
  tags:
 
 
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  - generated_from_trainer
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  model-index:
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  - name: ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53
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  # ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53
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+ This model is a fine-tuned version of [gary109/ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53](https://huggingface.co/gary109/ai-light-dance_singing3_ft_pretrain2_wav2vec2-large-xlsr-53) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.5938
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+ - Wer: 1.0156
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 1.209 | 1.0 | 72 | 2.5599 | 0.9889 |
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+ | 1.3395 | 2.0 | 144 | 2.7188 | 0.9877 |
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+ | 1.2695 | 3.0 | 216 | 2.9989 | 0.9709 |
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+ | 1.2818 | 4.0 | 288 | 3.2352 | 0.9757 |
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+ | 1.2389 | 5.0 | 360 | 3.6867 | 0.9783 |
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+ | 1.2368 | 6.0 | 432 | 3.3189 | 0.9811 |
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+ | 1.2307 | 7.0 | 504 | 3.0786 | 0.9657 |
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+ | 1.2607 | 8.0 | 576 | 2.9720 | 0.9677 |
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+ | 1.2584 | 9.0 | 648 | 2.5613 | 0.9702 |
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+ | 1.2266 | 10.0 | 720 | 2.6937 | 0.9610 |
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+ | 1.262 | 11.0 | 792 | 3.9060 | 0.9745 |
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+ | 1.2361 | 12.0 | 864 | 3.6138 | 0.9718 |
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+ | 1.2348 | 13.0 | 936 | 3.4838 | 0.9745 |
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+ | 1.2715 | 14.0 | 1008 | 3.3128 | 0.9751 |
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+ | 1.2505 | 15.0 | 1080 | 3.2015 | 0.9710 |
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+ | 1.211 | 16.0 | 1152 | 3.4709 | 0.9709 |
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+ | 1.2067 | 17.0 | 1224 | 3.0566 | 0.9673 |
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+ | 1.2536 | 18.0 | 1296 | 2.5479 | 0.9789 |
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+ | 1.2297 | 19.0 | 1368 | 2.8307 | 0.9710 |
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+ | 1.1949 | 20.0 | 1440 | 3.4112 | 0.9777 |
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+ | 1.2181 | 21.0 | 1512 | 2.6784 | 0.9682 |
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+ | 1.195 | 22.0 | 1584 | 3.0395 | 0.9639 |
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+ | 1.2047 | 23.0 | 1656 | 3.1935 | 0.9726 |
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+ | 1.2306 | 24.0 | 1728 | 3.2649 | 0.9723 |
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+ | 1.199 | 25.0 | 1800 | 3.1378 | 0.9645 |
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+ | 1.1945 | 26.0 | 1872 | 2.8143 | 0.9596 |
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+ | 1.19 | 27.0 | 1944 | 3.5174 | 0.9787 |
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+ | 1.1976 | 28.0 | 2016 | 2.9666 | 0.9594 |
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+ | 1.2229 | 29.0 | 2088 | 2.8672 | 0.9589 |
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+ | 1.1548 | 30.0 | 2160 | 2.6568 | 0.9627 |
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+ | 1.169 | 31.0 | 2232 | 2.8799 | 0.9654 |
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+ | 1.1857 | 32.0 | 2304 | 2.8691 | 0.9625 |
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+ | 1.1862 | 33.0 | 2376 | 2.8251 | 0.9555 |
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+ | 1.1721 | 34.0 | 2448 | 3.5968 | 0.9726 |
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+ | 1.1293 | 35.0 | 2520 | 3.4130 | 0.9651 |
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+ | 1.1513 | 36.0 | 2592 | 2.8804 | 0.9630 |
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+ | 1.1537 | 37.0 | 2664 | 2.5824 | 0.9575 |
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+ | 1.1818 | 38.0 | 2736 | 2.8443 | 0.9613 |
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+ | 1.1835 | 39.0 | 2808 | 2.6431 | 0.9619 |
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+ | 1.1457 | 40.0 | 2880 | 2.9254 | 0.9639 |
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+ | 1.1591 | 41.0 | 2952 | 2.8194 | 0.9561 |
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+ | 1.1284 | 42.0 | 3024 | 2.6432 | 0.9806 |
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+ | 1.1602 | 43.0 | 3096 | 2.4279 | 1.0087 |
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+ | 1.1556 | 44.0 | 3168 | 2.5040 | 1.0030 |
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+ | 1.1256 | 45.0 | 3240 | 3.1641 | 0.9608 |
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+ | 1.1256 | 46.0 | 3312 | 2.9522 | 0.9677 |
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+ | 1.1211 | 47.0 | 3384 | 2.6318 | 0.9580 |
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+ | 1.1142 | 48.0 | 3456 | 2.7298 | 0.9533 |
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+ | 1.1237 | 49.0 | 3528 | 2.5442 | 0.9673 |
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+ | 1.0976 | 50.0 | 3600 | 2.7767 | 0.9610 |
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+ | 1.1154 | 51.0 | 3672 | 2.6849 | 0.9646 |
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+ | 1.1012 | 52.0 | 3744 | 2.5384 | 0.9621 |
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+ | 1.1077 | 53.0 | 3816 | 2.4505 | 1.0067 |
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+ | 1.0936 | 54.0 | 3888 | 2.5847 | 0.9687 |
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+ | 1.0772 | 55.0 | 3960 | 2.4575 | 0.9761 |
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+ | 1.092 | 56.0 | 4032 | 2.4889 | 0.9802 |
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+ | 1.0868 | 57.0 | 4104 | 2.5885 | 0.9664 |
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+ | 1.0979 | 58.0 | 4176 | 2.6370 | 0.9607 |
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+ | 1.094 | 59.0 | 4248 | 2.6195 | 0.9605 |
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+ | 1.0745 | 60.0 | 4320 | 2.5346 | 0.9834 |
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+ | 1.1057 | 61.0 | 4392 | 2.6879 | 0.9603 |
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+ | 1.0722 | 62.0 | 4464 | 2.5426 | 0.9735 |
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+ | 1.0731 | 63.0 | 4536 | 2.8259 | 0.9535 |
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+ | 1.0862 | 64.0 | 4608 | 2.7632 | 0.9559 |
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+ | 1.0396 | 65.0 | 4680 | 2.5401 | 0.9807 |
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+ | 1.0581 | 66.0 | 4752 | 2.6977 | 0.9687 |
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+ | 1.0647 | 67.0 | 4824 | 2.6968 | 0.9694 |
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+ | 1.0549 | 68.0 | 4896 | 2.6439 | 0.9807 |
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+ | 1.0607 | 69.0 | 4968 | 2.6822 | 0.9771 |
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+ | 1.05 | 70.0 | 5040 | 2.7011 | 0.9607 |
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+ | 1.042 | 71.0 | 5112 | 2.5766 | 0.9713 |
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+ | 1.042 | 72.0 | 5184 | 2.5720 | 0.9747 |
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+ | 1.0594 | 73.0 | 5256 | 2.7176 | 0.9704 |
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+ | 1.0425 | 74.0 | 5328 | 2.7458 | 0.9614 |
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+ | 1.0199 | 75.0 | 5400 | 2.5906 | 0.9987 |
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+ | 1.0198 | 76.0 | 5472 | 2.5534 | 1.0087 |
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+ | 1.0193 | 77.0 | 5544 | 2.5421 | 0.9933 |
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+ | 1.0379 | 78.0 | 5616 | 2.5139 | 0.9994 |
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+ | 1.025 | 79.0 | 5688 | 2.4850 | 1.0313 |
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+ | 1.0054 | 80.0 | 5760 | 2.5803 | 0.9814 |
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+ | 1.0218 | 81.0 | 5832 | 2.5696 | 0.9867 |
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+ | 1.0177 | 82.0 | 5904 | 2.6011 | 1.0065 |
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+ | 1.0094 | 83.0 | 5976 | 2.6166 | 0.9855 |
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+ | 1.0202 | 84.0 | 6048 | 2.5557 | 1.0204 |
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+ | 1.0148 | 85.0 | 6120 | 2.6118 | 1.0033 |
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+ | 1.0117 | 86.0 | 6192 | 2.5671 | 1.0120 |
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+ | 1.0195 | 87.0 | 6264 | 2.5443 | 1.0041 |
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+ | 1.0114 | 88.0 | 6336 | 2.5627 | 1.0049 |
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+ | 1.0074 | 89.0 | 6408 | 2.5670 | 1.0255 |
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+ | 0.9883 | 90.0 | 6480 | 2.5338 | 1.0306 |
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+ | 1.0112 | 91.0 | 6552 | 2.5615 | 1.0142 |
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+ | 0.9986 | 92.0 | 6624 | 2.5566 | 1.0415 |
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+ | 0.9939 | 93.0 | 6696 | 2.5728 | 1.0287 |
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+ | 0.9954 | 94.0 | 6768 | 2.5617 | 1.0138 |
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+ | 0.9643 | 95.0 | 6840 | 2.5890 | 1.0145 |
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+ | 0.9892 | 96.0 | 6912 | 2.5918 | 1.0119 |
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+ | 0.983 | 97.0 | 6984 | 2.5862 | 1.0175 |
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+ | 0.988 | 98.0 | 7056 | 2.5873 | 1.0147 |
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+ | 0.9908 | 99.0 | 7128 | 2.5973 | 1.0073 |
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+ | 0.9696 | 100.0 | 7200 | 2.5938 | 1.0156 |
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  ### Framework versions