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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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datasets:
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- ai_light_dance
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- wer
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model-index:
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- name: ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-v6-1
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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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# ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-v6-1
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This model is a fine-tuned version of [gary109/ai-light-
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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: 0.
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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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:
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- num_epochs: 100.0
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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---
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tags:
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- generated_from_trainer
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datasets:
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- ai_light_dance
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- wer
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model-index:
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- name: ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-v6-1
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: ai_light_dance
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type: ai_light_dance
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config: onset-idmt-mdb-enst2
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split: train
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args: onset-idmt-mdb-enst2
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metrics:
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- name: Wer
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type: wer
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value: 0.32686630113876003
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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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# ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-v6-1
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This model is a fine-tuned version of [gary109/ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-v6-1](https://huggingface.co/gary109/ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-v6-1) on the ai_light_dance dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6187
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- Wer: 0.3269
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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: 0.0001
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 4
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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: 10
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- num_epochs: 100.0
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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 | Wer |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|
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| 0.2764 | 1.0 | 141 | 0.7125 | 0.3619 |
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| 0.5415 | 2.0 | 282 | 0.7252 | 0.3682 |
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| 0.3324 | 3.0 | 423 | 0.6779 | 0.3728 |
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| 0.4244 | 4.0 | 564 | 0.7403 | 0.3737 |
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| 0.5234 | 5.0 | 705 | 0.8086 | 0.3534 |
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| 0.3339 | 6.0 | 846 | 0.7187 | 0.3619 |
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| 0.5016 | 7.0 | 987 | 0.8582 | 0.3602 |
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| 0.3376 | 8.0 | 1128 | 0.8801 | 0.3674 |
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| 0.3507 | 9.0 | 1269 | 0.8524 | 0.3560 |
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| 0.4844 | 10.0 | 1410 | 0.7152 | 0.3648 |
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| 0.4282 | 11.0 | 1551 | 0.6719 | 0.3475 |
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| 0.4398 | 12.0 | 1692 | 0.7130 | 0.3686 |
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| 0.331 | 13.0 | 1833 | 0.6425 | 0.3627 |
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| 0.4488 | 14.0 | 1974 | 0.6483 | 0.3648 |
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| 0.3876 | 15.0 | 2115 | 0.6375 | 0.3509 |
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| 0.3361 | 16.0 | 2256 | 0.6791 | 0.3703 |
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| 0.344 | 17.0 | 2397 | 0.7279 | 0.3551 |
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| 0.3198 | 18.0 | 2538 | 0.6801 | 0.3509 |
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| 0.2753 | 19.0 | 2679 | 0.6239 | 0.3509 |
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| 0.2962 | 20.0 | 2820 | 0.7419 | 0.3442 |
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| 0.7503 | 21.0 | 2961 | 0.7279 | 0.3501 |
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| 0.4013 | 22.0 | 3102 | 0.6899 | 0.3792 |
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| 0.5134 | 23.0 | 3243 | 0.6572 | 0.3787 |
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| 0.3144 | 24.0 | 3384 | 0.5882 | 0.3543 |
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| 0.3534 | 25.0 | 3525 | 0.5661 | 0.3416 |
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| 0.2555 | 26.0 | 3666 | 0.5977 | 0.3589 |
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| 0.3524 | 27.0 | 3807 | 0.5953 | 0.3585 |
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| 0.314 | 28.0 | 3948 | 0.6359 | 0.3593 |
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| 0.2565 | 29.0 | 4089 | 0.6192 | 0.3615 |
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| 0.5023 | 30.0 | 4230 | 0.6229 | 0.3378 |
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| 0.3025 | 31.0 | 4371 | 0.6002 | 0.3442 |
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| 0.3329 | 32.0 | 4512 | 0.6235 | 0.3513 |
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| 0.3744 | 33.0 | 4653 | 0.5782 | 0.3416 |
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| 0.2899 | 34.0 | 4794 | 0.5835 | 0.3336 |
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| 0.306 | 35.0 | 4935 | 0.6061 | 0.3496 |
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| 0.2519 | 36.0 | 5076 | 0.5958 | 0.3652 |
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| 0.3201 | 37.0 | 5217 | 0.5778 | 0.3652 |
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| 0.3011 | 38.0 | 5358 | 0.6238 | 0.3589 |
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| 0.2882 | 39.0 | 5499 | 0.6501 | 0.3361 |
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| 0.2542 | 40.0 | 5640 | 0.6341 | 0.3488 |
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| 0.2717 | 41.0 | 5781 | 0.5890 | 0.3530 |
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| 0.3197 | 42.0 | 5922 | 0.5877 | 0.3471 |
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| 0.2816 | 43.0 | 6063 | 0.6614 | 0.3420 |
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| 0.3301 | 44.0 | 6204 | 0.6334 | 0.3475 |
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| 0.2466 | 45.0 | 6345 | 0.6663 | 0.3429 |
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| 0.2908 | 46.0 | 6486 | 0.5941 | 0.3475 |
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| 0.2785 | 47.0 | 6627 | 0.6337 | 0.3568 |
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| 0.2361 | 48.0 | 6768 | 0.5845 | 0.3399 |
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| 0.4729 | 49.0 | 6909 | 0.6466 | 0.3425 |
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| 0.5103 | 50.0 | 7050 | 0.7112 | 0.3416 |
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| 0.2676 | 51.0 | 7191 | 0.6260 | 0.3307 |
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| 0.3533 | 52.0 | 7332 | 0.7327 | 0.3454 |
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| 0.3308 | 53.0 | 7473 | 0.7150 | 0.3277 |
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| 0.2617 | 54.0 | 7614 | 0.6412 | 0.3391 |
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| 0.2901 | 55.0 | 7755 | 0.6225 | 0.3391 |
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| 0.2847 | 56.0 | 7896 | 0.7385 | 0.3391 |
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| 0.2621 | 57.0 | 8037 | 0.7241 | 0.3496 |
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| 0.2477 | 58.0 | 8178 | 0.6957 | 0.3429 |
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| 0.3147 | 59.0 | 8319 | 0.6808 | 0.3425 |
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| 0.3761 | 60.0 | 8460 | 0.6710 | 0.3450 |
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| 0.2609 | 61.0 | 8601 | 0.6629 | 0.3345 |
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| 0.388 | 62.0 | 8742 | 0.6688 | 0.3463 |
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| 0.3684 | 63.0 | 8883 | 0.7018 | 0.3340 |
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| 0.2494 | 64.0 | 9024 | 0.6611 | 0.3399 |
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| 0.2641 | 65.0 | 9165 | 0.6828 | 0.3399 |
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| 0.2716 | 66.0 | 9306 | 0.6409 | 0.3294 |
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| 0.2595 | 67.0 | 9447 | 0.6056 | 0.3231 |
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| 0.2683 | 68.0 | 9588 | 0.6203 | 0.3332 |
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| 0.2571 | 69.0 | 9729 | 0.6484 | 0.3336 |
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| 0.2593 | 70.0 | 9870 | 0.6597 | 0.3294 |
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| 0.229 | 71.0 | 10011 | 0.6354 | 0.3235 |
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| 0.281 | 72.0 | 10152 | 0.6398 | 0.3294 |
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| 0.3779 | 73.0 | 10293 | 0.6871 | 0.3345 |
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| 0.2998 | 74.0 | 10434 | 0.7329 | 0.3323 |
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| 0.2095 | 75.0 | 10575 | 0.7365 | 0.3239 |
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| 0.247 | 76.0 | 10716 | 0.6384 | 0.3290 |
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| 0.2095 | 77.0 | 10857 | 0.6703 | 0.3345 |
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| 0.2074 | 78.0 | 10998 | 0.6577 | 0.3425 |
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| 0.2519 | 79.0 | 11139 | 0.6359 | 0.3370 |
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| 0.2046 | 80.0 | 11280 | 0.6222 | 0.3256 |
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| 1.3195 | 81.0 | 11421 | 0.6126 | 0.3345 |
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| 0.2821 | 82.0 | 11562 | 0.6193 | 0.3294 |
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| 0.3256 | 83.0 | 11703 | 0.6140 | 0.3336 |
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| 0.2743 | 84.0 | 11844 | 0.6204 | 0.3290 |
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| 0.2761 | 85.0 | 11985 | 0.6599 | 0.3252 |
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| 0.224 | 86.0 | 12126 | 0.6580 | 0.3294 |
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| 0.2106 | 87.0 | 12267 | 0.6298 | 0.3294 |
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| 0.2706 | 88.0 | 12408 | 0.6411 | 0.3281 |
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| 0.2523 | 89.0 | 12549 | 0.6243 | 0.3264 |
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| 0.3635 | 90.0 | 12690 | 0.6297 | 0.3290 |
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| 0.353 | 91.0 | 12831 | 0.6145 | 0.3235 |
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| 0.2491 | 92.0 | 12972 | 0.6296 | 0.3197 |
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| 0.1999 | 93.0 | 13113 | 0.6329 | 0.3222 |
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| 0.2417 | 94.0 | 13254 | 0.6200 | 0.3222 |
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| 0.2397 | 95.0 | 13395 | 0.6137 | 0.3269 |
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| 0.2275 | 96.0 | 13536 | 0.6237 | 0.3277 |
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| 0.207 | 97.0 | 13677 | 0.6230 | 0.3235 |
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| 0.2704 | 98.0 | 13818 | 0.6239 | 0.3281 |
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| 0.2119 | 99.0 | 13959 | 0.6224 | 0.3277 |
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| 0.2561 | 100.0 | 14100 | 0.6187 | 0.3269 |
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### Framework versions
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