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README.md
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---
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license: apache-2.0
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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_wav2vec2-large-xlsr-53-v1-5gram
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# ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram
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This model is a fine-tuned version of [gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram](https://huggingface.co/gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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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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- lr_scheduler_warmup_steps: 100
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### Training results
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### Framework versions
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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: ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram
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# ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram
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This model is a fine-tuned version of [gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram](https://huggingface.co/gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4671
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- Wer: 0.1972
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 8
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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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- lr_scheduler_warmup_steps: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|
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| 0.2733 | 1.0 | 578 | 0.4485 | 0.2136 |
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| 0.3215 | 2.0 | 1156 | 0.4449 | 0.2121 |
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| 0.3305 | 3.0 | 1734 | 0.4521 | 0.2116 |
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| 0.3208 | 4.0 | 2312 | 0.4548 | 0.2106 |
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| 0.2838 | 5.0 | 2890 | 0.4509 | 0.2088 |
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| 0.3179 | 6.0 | 3468 | 0.4532 | 0.2089 |
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| 0.3352 | 7.0 | 4046 | 0.4527 | 0.2081 |
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| 0.3406 | 8.0 | 4624 | 0.4531 | 0.2092 |
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| 0.3163 | 9.0 | 5202 | 0.4546 | 0.2085 |
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| 0.3288 | 10.0 | 5780 | 0.4548 | 0.2061 |
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| 0.3073 | 11.0 | 6358 | 0.4525 | 0.2065 |
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| 0.3102 | 12.0 | 6936 | 0.4526 | 0.2065 |
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| 0.3113 | 13.0 | 7514 | 0.4534 | 0.2045 |
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| 0.2968 | 14.0 | 8092 | 0.4554 | 0.2077 |
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| 0.2902 | 15.0 | 8670 | 0.4509 | 0.2067 |
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| 0.2832 | 16.0 | 9248 | 0.4557 | 0.2047 |
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| 0.3147 | 17.0 | 9826 | 0.4584 | 0.2054 |
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| 0.3073 | 18.0 | 10404 | 0.4554 | 0.2038 |
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| 0.3105 | 19.0 | 10982 | 0.4581 | 0.2040 |
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| 0.2435 | 20.0 | 11560 | 0.4582 | 0.2044 |
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| 0.3005 | 21.0 | 12138 | 0.4599 | 0.2037 |
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| 0.3133 | 22.0 | 12716 | 0.4640 | 0.2032 |
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| 0.2831 | 23.0 | 13294 | 0.4597 | 0.2037 |
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| 0.2852 | 24.0 | 13872 | 0.4574 | 0.2020 |
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| 0.3473 | 25.0 | 14450 | 0.4567 | 0.2045 |
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| 0.2958 | 26.0 | 15028 | 0.4592 | 0.2034 |
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| 0.2802 | 27.0 | 15606 | 0.4590 | 0.2035 |
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| 0.2932 | 28.0 | 16184 | 0.4632 | 0.2015 |
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| 0.3167 | 29.0 | 16762 | 0.4627 | 0.2034 |
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| 0.3381 | 30.0 | 17340 | 0.4617 | 0.2038 |
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| 0.3245 | 31.0 | 17918 | 0.4616 | 0.2031 |
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| 0.3075 | 32.0 | 18496 | 0.4567 | 0.2035 |
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| 0.2895 | 33.0 | 19074 | 0.4574 | 0.2031 |
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| 0.3034 | 34.0 | 19652 | 0.4598 | 0.2019 |
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| 0.2624 | 35.0 | 20230 | 0.4624 | 0.2002 |
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| 0.2888 | 36.0 | 20808 | 0.4628 | 0.2019 |
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| 0.2627 | 37.0 | 21386 | 0.4619 | 0.2015 |
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| 0.2644 | 38.0 | 21964 | 0.4591 | 0.2027 |
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| 0.3187 | 39.0 | 22542 | 0.4562 | 0.2001 |
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| 0.299 | 40.0 | 23120 | 0.4588 | 0.2008 |
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| 0.3088 | 41.0 | 23698 | 0.4616 | 0.2017 |
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| 0.2602 | 42.0 | 24276 | 0.4621 | 0.2006 |
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| 0.2709 | 43.0 | 24854 | 0.4613 | 0.2009 |
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| 0.314 | 44.0 | 25432 | 0.4612 | 0.2004 |
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| 0.2568 | 45.0 | 26010 | 0.4632 | 0.1997 |
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| 0.3231 | 46.0 | 26588 | 0.4597 | 0.2007 |
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| 0.2927 | 47.0 | 27166 | 0.4610 | 0.2002 |
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| 0.289 | 48.0 | 27744 | 0.4649 | 0.2006 |
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| 0.2764 | 49.0 | 28322 | 0.4645 | 0.2011 |
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| 0.2562 | 50.0 | 28900 | 0.4655 | 0.2011 |
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| 0.3026 | 51.0 | 29478 | 0.4697 | 0.2005 |
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| 0.3019 | 52.0 | 30056 | 0.4676 | 0.2004 |
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| 0.2863 | 53.0 | 30634 | 0.4643 | 0.2002 |
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| 0.3016 | 54.0 | 31212 | 0.4674 | 0.2007 |
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| 0.2963 | 55.0 | 31790 | 0.4671 | 0.1998 |
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| 0.3089 | 56.0 | 32368 | 0.4654 | 0.1993 |
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| 0.2641 | 57.0 | 32946 | 0.4652 | 0.1993 |
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| 0.2805 | 58.0 | 33524 | 0.4635 | 0.1984 |
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| 0.2871 | 59.0 | 34102 | 0.4648 | 0.2006 |
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| 0.3335 | 60.0 | 34680 | 0.4658 | 0.1994 |
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| 0.3089 | 61.0 | 35258 | 0.4669 | 0.2004 |
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| 0.3108 | 62.0 | 35836 | 0.4652 | 0.1992 |
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| 0.274 | 63.0 | 36414 | 0.4641 | 0.1995 |
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| 0.2828 | 64.0 | 36992 | 0.4640 | 0.1993 |
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| 0.2683 | 65.0 | 37570 | 0.4632 | 0.1986 |
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| 0.267 | 66.0 | 38148 | 0.4667 | 0.1983 |
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| 0.2983 | 67.0 | 38726 | 0.4670 | 0.1986 |
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| 0.2877 | 68.0 | 39304 | 0.4661 | 0.1997 |
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| 0.3047 | 69.0 | 39882 | 0.4669 | 0.1997 |
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| 0.2883 | 70.0 | 40460 | 0.4689 | 0.1987 |
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| 0.2893 | 71.0 | 41038 | 0.4661 | 0.1988 |
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| 0.3166 | 72.0 | 41616 | 0.4676 | 0.1993 |
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| 0.2811 | 73.0 | 42194 | 0.4670 | 0.1988 |
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| 0.2734 | 74.0 | 42772 | 0.4667 | 0.1991 |
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| 0.2786 | 75.0 | 43350 | 0.4685 | 0.1982 |
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| 0.2656 | 76.0 | 43928 | 0.4684 | 0.1981 |
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| 0.3256 | 77.0 | 44506 | 0.4685 | 0.1986 |
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| 0.2976 | 78.0 | 45084 | 0.4680 | 0.1977 |
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| 0.292 | 79.0 | 45662 | 0.4676 | 0.1971 |
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| 0.2998 | 80.0 | 46240 | 0.4673 | 0.1984 |
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| 0.2931 | 81.0 | 46818 | 0.4682 | 0.1990 |
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| 0.3054 | 82.0 | 47396 | 0.4680 | 0.1997 |
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| 0.3088 | 83.0 | 47974 | 0.4672 | 0.1982 |
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| 0.315 | 84.0 | 48552 | 0.4679 | 0.1974 |
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| 0.3334 | 85.0 | 49130 | 0.4670 | 0.1973 |
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| 0.2757 | 86.0 | 49708 | 0.4664 | 0.1980 |
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| 0.2928 | 87.0 | 50286 | 0.4670 | 0.1977 |
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| 0.2926 | 88.0 | 50864 | 0.4671 | 0.1982 |
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| 0.2866 | 89.0 | 51442 | 0.4667 | 0.1972 |
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| 0.2737 | 90.0 | 52020 | 0.4675 | 0.1973 |
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| 0.273 | 91.0 | 52598 | 0.4672 | 0.1985 |
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| 0.2936 | 92.0 | 53176 | 0.4672 | 0.1985 |
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| 0.2874 | 93.0 | 53754 | 0.4681 | 0.1980 |
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| 0.257 | 94.0 | 54332 | 0.4675 | 0.1978 |
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| 0.259 | 95.0 | 54910 | 0.4669 | 0.1980 |
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| 0.2689 | 96.0 | 55488 | 0.4670 | 0.1970 |
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| 0.2949 | 97.0 | 56066 | 0.4670 | 0.1978 |
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| 0.2977 | 98.0 | 56644 | 0.4668 | 0.1980 |
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| 0.2511 | 99.0 | 57222 | 0.4669 | 0.1970 |
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| 0.2598 | 100.0 | 57800 | 0.4671 | 0.1972 |
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### Framework versions
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