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Automatic Speech Recognition
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PyTorch
TensorBoard
wav2vec2
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update model card README.md

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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3440
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  - Wer: 1
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  ## Model description
@@ -52,56 +52,56 @@ 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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- | 16.8292 | 1.56 | 100 | 16.7197 | 1 |
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- | 15.1534 | 3.12 | 200 | 14.3410 | 1 |
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- | 10.7755 | 4.69 | 300 | 9.9820 | 1 |
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- | 6.4859 | 6.25 | 400 | 6.1913 | 1 |
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- | 4.0464 | 7.81 | 500 | 3.8280 | 1 |
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- | 3.3418 | 9.38 | 600 | 3.2733 | 1 |
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- | 3.217 | 10.94 | 700 | 3.1409 | 1 |
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- | 3.0927 | 12.5 | 800 | 3.0469 | 1 |
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- | 3.0235 | 14.06 | 900 | 3.0015 | 1 |
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- | 2.9902 | 15.62 | 1000 | 2.9748 | 1 |
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- | 2.945 | 17.19 | 1100 | 2.9550 | 1 |
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- | 2.9293 | 18.75 | 1200 | 2.9262 | 1 |
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- | 2.9139 | 20.31 | 1300 | 2.9230 | 1 |
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- | 2.9084 | 21.88 | 1400 | 2.9067 | 1 |
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- | 2.8941 | 23.44 | 1500 | 2.9077 | 1 |
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- | 2.8883 | 25.0 | 1600 | 2.8858 | 1 |
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- | 2.872 | 26.56 | 1700 | 2.8709 | 1 |
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- | 2.8641 | 28.12 | 1800 | 2.8587 | 1 |
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- | 2.8548 | 29.69 | 1900 | 2.8537 | 1 |
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- | 2.8396 | 31.25 | 2000 | 2.8371 | 1 |
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- | 2.7043 | 32.81 | 2100 | 2.6063 | 1 |
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- | 2.3905 | 34.38 | 2200 | 2.2233 | 1 |
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- | 1.9862 | 35.94 | 2300 | 1.7478 | 1 |
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- | 1.5463 | 37.5 | 2400 | 1.3176 | 1 |
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- | 1.218 | 39.06 | 2500 | 0.9948 | 1 |
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- | 0.9606 | 40.62 | 2600 | 0.7820 | 1 |
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- | 0.7923 | 42.19 | 2700 | 0.6577 | 1 |
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- | 0.6811 | 43.75 | 2800 | 0.5650 | 1 |
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- | 0.5927 | 45.31 | 2900 | 0.5204 | 1 |
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- | 0.5449 | 46.88 | 3000 | 0.4857 | 1 |
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- | 0.4876 | 48.44 | 3100 | 0.4526 | 1 |
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- | 0.4646 | 50.0 | 3200 | 0.4281 | 1 |
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- | 0.4374 | 51.56 | 3300 | 0.4376 | 1 |
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- | 0.3952 | 53.12 | 3400 | 0.4075 | 1 |
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- | 0.3952 | 54.69 | 3500 | 0.3937 | 1 |
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- | 0.3558 | 56.25 | 3600 | 0.3875 | 1 |
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- | 0.3527 | 57.81 | 3700 | 0.3775 | 1 |
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- | 0.3349 | 59.38 | 3800 | 0.3701 | 1 |
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- | 0.3264 | 60.94 | 3900 | 0.3576 | 1 |
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- | 0.3108 | 62.5 | 4000 | 0.3644 | 1 |
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- | 0.3104 | 64.06 | 4100 | 0.3548 | 1 |
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- | 0.3012 | 65.62 | 4200 | 0.3510 | 1 |
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- | 0.3027 | 67.19 | 4300 | 0.3486 | 1 |
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- | 0.2967 | 68.75 | 4400 | 0.3431 | 1 |
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- | 0.2892 | 70.31 | 4500 | 0.3391 | 1 |
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- | 0.296 | 71.88 | 4600 | 0.3427 | 1 |
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- | 0.2821 | 73.44 | 4700 | 0.3469 | 1 |
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- | 0.2701 | 75.0 | 4800 | 0.3428 | 1 |
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- | 0.2825 | 76.56 | 4900 | 0.3426 | 1 |
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- | 0.2549 | 78.12 | 5000 | 0.3440 | 1 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3836
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  - Wer: 1
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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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+ | 23.2159 | 0.6 | 100 | 22.1148 | 1 |
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+ | 18.1848 | 1.2 | 200 | 16.7223 | 1 |
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+ | 9.7817 | 1.8 | 300 | 7.9404 | 1 |
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+ | 4.5091 | 2.4 | 400 | 3.7900 | 1 |
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+ | 3.4946 | 2.99 | 500 | 3.2953 | 1 |
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+ | 3.3286 | 3.59 | 600 | 3.1827 | 1 |
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+ | 3.2078 | 4.19 | 700 | 3.1068 | 1 |
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+ | 3.1528 | 4.79 | 800 | 3.0573 | 1 |
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+ | 3.0709 | 5.39 | 900 | 3.0196 | 1 |
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+ | 3.0163 | 5.99 | 1000 | 2.9919 | 1 |
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+ | 2.9789 | 6.59 | 1100 | 2.9504 | 1 |
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+ | 2.9468 | 7.19 | 1200 | 2.9272 | 1 |
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+ | 2.9389 | 7.78 | 1300 | 2.9129 | 1 |
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+ | 2.9192 | 8.38 | 1400 | 2.9005 | 1 |
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+ | 2.9069 | 8.98 | 1500 | 2.8861 | 1 |
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+ | 2.9074 | 9.58 | 1600 | 2.8816 | 1 |
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+ | 2.883 | 10.18 | 1700 | 2.8746 | 1 |
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+ | 2.8746 | 10.78 | 1800 | 2.8718 | 1 |
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+ | 2.8637 | 11.38 | 1900 | 2.8567 | 1 |
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+ | 2.8613 | 11.98 | 2000 | 2.8570 | 1 |
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+ | 2.8598 | 12.57 | 2100 | 2.8449 | 1 |
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+ | 2.8357 | 13.17 | 2200 | 2.8393 | 1 |
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+ | 2.8352 | 13.77 | 2300 | 2.8350 | 1 |
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+ | 2.8178 | 14.37 | 2400 | 2.7879 | 1 |
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+ | 2.5089 | 14.97 | 2500 | 2.3686 | 1 |
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+ | 2.0826 | 15.57 | 2600 | 1.8915 | 1 |
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+ | 1.6003 | 16.17 | 2700 | 1.3513 | 1 |
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+ | 1.2925 | 16.77 | 2800 | 1.0568 | 1 |
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+ | 1.0837 | 17.37 | 2900 | 0.8760 | 1 |
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+ | 0.9333 | 17.96 | 3000 | 0.7588 | 1 |
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+ | 0.8214 | 18.56 | 3100 | 0.6841 | 1 |
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+ | 0.7302 | 19.16 | 3200 | 0.6099 | 1 |
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+ | 0.6815 | 19.76 | 3300 | 0.5459 | 1 |
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+ | 0.6548 | 20.36 | 3400 | 0.5087 | 1 |
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+ | 0.569 | 20.96 | 3500 | 0.4853 | 1 |
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+ | 0.5919 | 21.56 | 3600 | 0.4666 | 1 |
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+ | 0.5306 | 22.16 | 3700 | 0.4508 | 1 |
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+ | 0.5228 | 22.75 | 3800 | 0.4389 | 1 |
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+ | 0.5263 | 23.35 | 3900 | 0.4287 | 1 |
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+ | 0.4945 | 23.95 | 4000 | 0.4182 | 1 |
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+ | 0.4809 | 24.55 | 4100 | 0.4122 | 1 |
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+ | 0.4813 | 25.15 | 4200 | 0.4112 | 1 |
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+ | 0.4664 | 25.75 | 4300 | 0.3972 | 1 |
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+ | 0.455 | 26.35 | 4400 | 0.3950 | 1 |
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+ | 0.4415 | 26.95 | 4500 | 0.3962 | 1 |
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+ | 0.4399 | 27.54 | 4600 | 0.3930 | 1 |
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+ | 0.4451 | 28.14 | 4700 | 0.3864 | 1 |
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+ | 0.4343 | 28.74 | 4800 | 0.3867 | 1 |
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+ | 0.4418 | 29.34 | 4900 | 0.3865 | 1 |
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+ | 0.4223 | 29.94 | 5000 | 0.3836 | 1 |
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  ### Framework versions