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wav2vec2_XLSR_darija_maroc

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
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khaoulaoub commited on
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End of training

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  1. README.md +38 -38
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2860
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- - Wer: 0.3290
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  ## Model description
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@@ -52,42 +52,42 @@ 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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- | 4.9354 | 0.83 | 400 | 2.0492 | 1.0371 |
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- | 0.8236 | 1.66 | 800 | 0.4434 | 0.5832 |
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- | 0.4821 | 2.49 | 1200 | 0.3597 | 0.5114 |
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- | 0.3823 | 3.32 | 1600 | 0.3265 | 0.4758 |
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- | 0.3231 | 4.15 | 2000 | 0.3149 | 0.4526 |
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- | 0.2854 | 4.97 | 2400 | 0.2797 | 0.4237 |
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- | 0.2529 | 5.8 | 2800 | 0.3027 | 0.4415 |
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- | 0.2493 | 6.63 | 3200 | 0.2926 | 0.4264 |
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- | 0.2138 | 7.46 | 3600 | 0.2857 | 0.4169 |
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- | 0.2067 | 8.29 | 4000 | 0.2743 | 0.4099 |
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- | 0.1898 | 9.12 | 4400 | 0.2798 | 0.3993 |
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- | 0.1755 | 9.95 | 4800 | 0.2800 | 0.3913 |
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- | 0.1603 | 10.78 | 5200 | 0.2709 | 0.3860 |
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- | 0.1608 | 11.61 | 5600 | 0.2716 | 0.3872 |
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- | 0.1462 | 12.44 | 6000 | 0.2697 | 0.3825 |
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- | 0.137 | 13.26 | 6400 | 0.2855 | 0.3819 |
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- | 0.1326 | 14.09 | 6800 | 0.2860 | 0.3733 |
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- | 0.123 | 14.92 | 7200 | 0.2677 | 0.3813 |
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- | 0.1168 | 15.75 | 7600 | 0.2780 | 0.3740 |
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- | 0.1113 | 16.58 | 8000 | 0.2926 | 0.3719 |
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- | 0.1057 | 17.41 | 8400 | 0.2927 | 0.3704 |
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- | 0.0996 | 18.24 | 8800 | 0.2825 | 0.3602 |
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- | 0.0967 | 19.07 | 9200 | 0.2983 | 0.3641 |
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- | 0.0925 | 19.9 | 9600 | 0.2843 | 0.3576 |
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- | 0.0894 | 20.73 | 10000 | 0.2726 | 0.3668 |
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- | 0.0836 | 21.55 | 10400 | 0.2829 | 0.3560 |
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- | 0.0789 | 22.38 | 10800 | 0.2806 | 0.3508 |
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- | 0.0778 | 23.21 | 11200 | 0.2849 | 0.3540 |
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- | 0.0742 | 24.04 | 11600 | 0.2770 | 0.3436 |
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- | 0.0679 | 24.87 | 12000 | 0.2850 | 0.3425 |
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- | 0.063 | 25.7 | 12400 | 0.2846 | 0.3366 |
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- | 0.0593 | 26.53 | 12800 | 0.2811 | 0.3351 |
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- | 0.0586 | 27.36 | 13200 | 0.2863 | 0.3322 |
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- | 0.0555 | 28.19 | 13600 | 0.2819 | 0.3311 |
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- | 0.053 | 29.02 | 14000 | 0.2874 | 0.3301 |
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- | 0.0498 | 29.84 | 14400 | 0.2860 | 0.3290 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2740
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+ - Wer: 0.3247
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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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+ | 4.9874 | 0.83 | 400 | 2.4916 | 0.9978 |
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+ | 0.9314 | 1.66 | 800 | 0.4379 | 0.5839 |
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+ | 0.4856 | 2.49 | 1200 | 0.3485 | 0.5001 |
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+ | 0.3859 | 3.32 | 1600 | 0.3331 | 0.4768 |
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+ | 0.3271 | 4.15 | 2000 | 0.2932 | 0.4369 |
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+ | 0.2842 | 4.97 | 2400 | 0.2988 | 0.4422 |
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+ | 0.2482 | 5.8 | 2800 | 0.2815 | 0.4174 |
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+ | 0.2252 | 6.63 | 3200 | 0.2967 | 0.4316 |
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+ | 0.2115 | 7.46 | 3600 | 0.2719 | 0.4007 |
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+ | 0.1965 | 8.29 | 4000 | 0.2867 | 0.3985 |
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+ | 0.1823 | 9.12 | 4400 | 0.2744 | 0.4008 |
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+ | 0.1712 | 9.95 | 4800 | 0.2589 | 0.3873 |
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+ | 0.156 | 10.78 | 5200 | 0.2589 | 0.3745 |
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+ | 0.1536 | 11.61 | 5600 | 0.2628 | 0.3799 |
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+ | 0.1404 | 12.44 | 6000 | 0.2704 | 0.3805 |
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+ | 0.1402 | 13.26 | 6400 | 0.2748 | 0.3784 |
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+ | 0.1305 | 14.09 | 6800 | 0.2780 | 0.3769 |
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+ | 0.121 | 14.92 | 7200 | 0.2760 | 0.3698 |
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+ | 0.1147 | 15.75 | 7600 | 0.2723 | 0.3733 |
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+ | 0.1076 | 16.58 | 8000 | 0.2661 | 0.3671 |
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+ | 0.1013 | 17.41 | 8400 | 0.2709 | 0.3665 |
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+ | 0.0964 | 18.24 | 8800 | 0.2748 | 0.3599 |
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+ | 0.0946 | 19.07 | 9200 | 0.2696 | 0.3550 |
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+ | 0.0916 | 19.9 | 9600 | 0.2649 | 0.3596 |
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+ | 0.0849 | 20.73 | 10000 | 0.2905 | 0.3573 |
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+ | 0.0803 | 21.55 | 10400 | 0.2646 | 0.3496 |
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+ | 0.0748 | 22.38 | 10800 | 0.2871 | 0.3486 |
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+ | 0.0739 | 23.21 | 11200 | 0.2751 | 0.3432 |
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+ | 0.0699 | 24.04 | 11600 | 0.2857 | 0.3426 |
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+ | 0.0637 | 24.87 | 12000 | 0.2690 | 0.3377 |
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+ | 0.0627 | 25.7 | 12400 | 0.2737 | 0.3371 |
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+ | 0.0601 | 26.53 | 12800 | 0.2752 | 0.3358 |
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+ | 0.0564 | 27.36 | 13200 | 0.2827 | 0.3329 |
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+ | 0.0536 | 28.19 | 13600 | 0.2764 | 0.3310 |
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+ | 0.0508 | 29.02 | 14000 | 0.2750 | 0.3281 |
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+ | 0.0495 | 29.84 | 14400 | 0.2740 | 0.3247 |
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  ### Framework versions
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