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README.md CHANGED
@@ -1,26 +1,21 @@
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  ---
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- language:
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- - en
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  license: mit
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  base_model: microsoft/speecht5_tts
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  tags:
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- - en_accent,mozilla,t5,common_voice_1_0
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  - generated_from_trainer
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- datasets:
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- - mozilla-foundation/common_voice_1_0
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  model-index:
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- - name: SpeechT5 TTS English Accented
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # SpeechT5 TTS English Accented
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- This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Common Voice dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3812
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  ## Model description
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@@ -53,66 +48,66 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:-----:|:---------------:|
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- | No log | 2.34 | 250 | 0.5148 |
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- | 0.5893 | 4.67 | 500 | 0.3786 |
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- | 0.5893 | 7.01 | 750 | 0.3621 |
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- | 0.4015 | 9.35 | 1000 | 0.3600 |
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- | 0.4015 | 11.68 | 1250 | 0.3701 |
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- | 0.3739 | 14.02 | 1500 | 0.3612 |
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- | 0.3739 | 16.36 | 1750 | 0.3626 |
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- | 0.3634 | 18.69 | 2000 | 0.3499 |
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- | 0.3634 | 21.03 | 2250 | 0.3549 |
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- | 0.3499 | 23.36 | 2500 | 0.3600 |
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- | 0.3499 | 25.7 | 2750 | 0.3533 |
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- | 0.3428 | 28.04 | 3000 | 0.3652 |
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- | 0.3428 | 30.37 | 3250 | 0.3541 |
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- | 0.3407 | 32.71 | 3500 | 0.3579 |
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- | 0.3407 | 35.05 | 3750 | 0.3550 |
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- | 0.3368 | 37.38 | 4000 | 0.3624 |
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- | 0.3368 | 39.72 | 4250 | 0.3621 |
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- | 0.3315 | 42.06 | 4500 | 0.3577 |
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- | 0.3315 | 44.39 | 4750 | 0.3620 |
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- | 0.3305 | 46.73 | 5000 | 0.3665 |
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- | 0.3305 | 49.07 | 5250 | 0.3641 |
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- | 0.3273 | 51.4 | 5500 | 0.3563 |
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- | 0.3273 | 53.74 | 5750 | 0.3579 |
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- | 0.3228 | 56.07 | 6000 | 0.3615 |
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- | 0.3228 | 58.41 | 6250 | 0.3606 |
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- | 0.3227 | 60.75 | 6500 | 0.3647 |
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- | 0.3227 | 63.08 | 6750 | 0.3647 |
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- | 0.3183 | 65.42 | 7000 | 0.3619 |
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- | 0.3183 | 67.76 | 7250 | 0.3786 |
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- | 0.3184 | 70.09 | 7500 | 0.3731 |
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- | 0.3184 | 72.43 | 7750 | 0.3630 |
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- | 0.3177 | 74.77 | 8000 | 0.3647 |
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- | 0.3177 | 77.1 | 8250 | 0.3668 |
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- | 0.3159 | 79.44 | 8500 | 0.3624 |
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- | 0.3159 | 81.78 | 8750 | 0.3742 |
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- | 0.3129 | 84.11 | 9000 | 0.3722 |
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- | 0.3129 | 86.45 | 9250 | 0.3755 |
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- | 0.3124 | 88.79 | 9500 | 0.3693 |
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- | 0.3124 | 91.12 | 9750 | 0.3707 |
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- | 0.3094 | 93.46 | 10000 | 0.3808 |
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- | 0.3094 | 95.79 | 10250 | 0.3696 |
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- | 0.3116 | 98.13 | 10500 | 0.3773 |
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- | 0.3116 | 100.47 | 10750 | 0.3796 |
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- | 0.3076 | 102.8 | 11000 | 0.3705 |
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- | 0.3076 | 105.14 | 11250 | 0.3718 |
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- | 0.3104 | 107.48 | 11500 | 0.3792 |
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- | 0.3104 | 109.81 | 11750 | 0.3714 |
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- | 0.3078 | 112.15 | 12000 | 0.3765 |
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- | 0.3078 | 114.49 | 12250 | 0.3803 |
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- | 0.3064 | 116.82 | 12500 | 0.3792 |
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- | 0.3064 | 119.16 | 12750 | 0.3803 |
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- | 0.3087 | 121.5 | 13000 | 0.3806 |
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- | 0.3087 | 123.83 | 13250 | 0.3821 |
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- | 0.3064 | 126.17 | 13500 | 0.3795 |
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- | 0.3064 | 128.5 | 13750 | 0.3766 |
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- | 0.3066 | 130.84 | 14000 | 0.3780 |
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- | 0.3066 | 133.18 | 14250 | 0.3858 |
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- | 0.3081 | 135.51 | 14500 | 0.3812 |
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- | 0.3081 | 137.85 | 14750 | 0.3829 |
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- | 0.3064 | 140.19 | 15000 | 0.3812 |
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  ### Framework versions
 
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  ---
 
 
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  license: mit
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  base_model: microsoft/speecht5_tts
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  tags:
 
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  - generated_from_trainer
 
 
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  model-index:
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+ - name: speecht5_tts
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # speecht5_tts
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+ This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6698
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:-----:|:---------------:|
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+ | No log | 11.36 | 250 | 0.7543 |
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+ | 0.7974 | 22.73 | 500 | 0.5421 |
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+ | 0.7974 | 34.09 | 750 | 0.5298 |
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+ | 0.5132 | 45.45 | 1000 | 0.5404 |
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+ | 0.5132 | 56.82 | 1250 | 0.5513 |
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+ | 0.4589 | 68.18 | 1500 | 0.5664 |
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+ | 0.4589 | 79.55 | 1750 | 0.5688 |
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+ | 0.4362 | 90.91 | 2000 | 0.6007 |
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+ | 0.4362 | 102.27 | 2250 | 0.5819 |
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+ | 0.4264 | 113.64 | 2500 | 0.5813 |
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+ | 0.4264 | 125.0 | 2750 | 0.6025 |
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+ | 0.4136 | 136.36 | 3000 | 0.6001 |
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+ | 0.4136 | 147.73 | 3250 | 0.5854 |
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+ | 0.4058 | 159.09 | 3500 | 0.6119 |
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+ | 0.4058 | 170.45 | 3750 | 0.6194 |
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+ | 0.3914 | 181.82 | 4000 | 0.6248 |
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+ | 0.3914 | 193.18 | 4250 | 0.6185 |
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+ | 0.3892 | 204.55 | 4500 | 0.6116 |
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+ | 0.3892 | 215.91 | 4750 | 0.6208 |
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+ | 0.3807 | 227.27 | 5000 | 0.6275 |
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+ | 0.3807 | 238.64 | 5250 | 0.6214 |
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+ | 0.378 | 250.0 | 5500 | 0.6209 |
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+ | 0.378 | 261.36 | 5750 | 0.6398 |
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+ | 0.3677 | 272.73 | 6000 | 0.6272 |
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+ | 0.3677 | 284.09 | 6250 | 0.6274 |
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+ | 0.3662 | 295.45 | 6500 | 0.6571 |
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+ | 0.3662 | 306.82 | 6750 | 0.6337 |
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+ | 0.3593 | 318.18 | 7000 | 0.6456 |
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+ | 0.3593 | 329.55 | 7250 | 0.6321 |
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+ | 0.3587 | 340.91 | 7500 | 0.6360 |
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+ | 0.3587 | 352.27 | 7750 | 0.6504 |
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+ | 0.3556 | 363.64 | 8000 | 0.6478 |
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+ | 0.3556 | 375.0 | 8250 | 0.6516 |
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+ | 0.3554 | 386.36 | 8500 | 0.6398 |
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+ | 0.3554 | 397.73 | 8750 | 0.6524 |
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+ | 0.3489 | 409.09 | 9000 | 0.6484 |
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+ | 0.3489 | 420.45 | 9250 | 0.6418 |
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+ | 0.3513 | 431.82 | 9500 | 0.6421 |
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+ | 0.3513 | 443.18 | 9750 | 0.6460 |
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+ | 0.3464 | 454.55 | 10000 | 0.6586 |
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+ | 0.3464 | 465.91 | 10250 | 0.6613 |
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+ | 0.3456 | 477.27 | 10500 | 0.6511 |
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+ | 0.3456 | 488.64 | 10750 | 0.6474 |
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+ | 0.3405 | 500.0 | 11000 | 0.6402 |
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+ | 0.3405 | 511.36 | 11250 | 0.6541 |
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+ | 0.3436 | 522.73 | 11500 | 0.6596 |
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+ | 0.3436 | 534.09 | 11750 | 0.6631 |
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+ | 0.3385 | 545.45 | 12000 | 0.6574 |
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+ | 0.3385 | 556.82 | 12250 | 0.6516 |
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+ | 0.3405 | 568.18 | 12500 | 0.6675 |
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+ | 0.3405 | 579.55 | 12750 | 0.6617 |
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+ | 0.3403 | 590.91 | 13000 | 0.6573 |
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+ | 0.3403 | 602.27 | 13250 | 0.6595 |
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+ | 0.336 | 613.64 | 13500 | 0.6625 |
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+ | 0.336 | 625.0 | 13750 | 0.6601 |
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+ | 0.3376 | 636.36 | 14000 | 0.6655 |
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+ | 0.3376 | 647.73 | 14250 | 0.6695 |
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+ | 0.3357 | 659.09 | 14500 | 0.6623 |
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+ | 0.3357 | 670.45 | 14750 | 0.6576 |
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+ | 0.3348 | 681.82 | 15000 | 0.6698 |
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  ### Framework versions
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