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hindi_wav2vec2_optimized

Automatic Speech Recognition
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PyTorch
wav2vec2
Generated from Trainer
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@@ -1,6 +1,6 @@
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  ---
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  license: mit
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- base_model: TheAIchemist13/hindi_beekeeping_wav2vec2
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # hindi_wav2vec2_optimized
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- This model is a fine-tuned version of [TheAIchemist13/hindi_beekeeping_wav2vec2](https://huggingface.co/TheAIchemist13/hindi_beekeeping_wav2vec2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6848
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- - Wer: 0.4059
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  ## Model description
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@@ -52,51 +52,51 @@ 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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- | 0.312 | 0.11 | 25 | 0.7359 | 0.4045 |
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- | 0.2789 | 0.22 | 50 | 0.7344 | 0.4129 |
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- | 0.3066 | 0.33 | 75 | 0.7687 | 0.4185 |
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- | 0.446 | 0.44 | 100 | 0.9725 | 0.4731 |
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- | 0.4249 | 0.54 | 125 | 1.2325 | 0.5073 |
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- | 1.2771 | 0.65 | 150 | 1.1657 | 0.5297 |
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- | 0.4671 | 0.76 | 175 | 0.9309 | 0.4759 |
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- | 0.759 | 0.87 | 200 | 1.0748 | 0.5038 |
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- | 0.4854 | 0.98 | 225 | 0.9735 | 0.4990 |
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- | 0.4588 | 1.09 | 250 | 0.8566 | 0.4717 |
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- | 1.429 | 1.2 | 275 | 0.8819 | 0.5073 |
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- | 0.495 | 1.31 | 300 | 0.8920 | 0.4710 |
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- | 0.3768 | 1.42 | 325 | 0.9280 | 0.4885 |
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- | 0.4792 | 1.53 | 350 | 0.9338 | 0.4689 |
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- | 0.4219 | 1.63 | 375 | 1.0726 | 0.5017 |
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- | 0.4818 | 1.74 | 400 | 0.9469 | 0.4913 |
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- | 0.4148 | 1.85 | 425 | 0.9698 | 0.5108 |
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- | 0.5901 | 1.96 | 450 | 0.9540 | 0.5129 |
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- | 0.4976 | 2.07 | 475 | 1.0502 | 0.5395 |
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- | 0.5696 | 2.18 | 500 | 0.8864 | 0.4675 |
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- | 0.4342 | 2.29 | 525 | 0.8964 | 0.4661 |
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- | 0.3418 | 2.4 | 550 | 0.9535 | 0.4941 |
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- | 0.5812 | 2.51 | 575 | 0.8451 | 0.4514 |
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- | 0.3522 | 2.61 | 600 | 0.9054 | 0.4864 |
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- | 0.4135 | 2.72 | 625 | 0.8788 | 0.4493 |
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- | 0.3061 | 2.83 | 650 | 0.8583 | 0.4570 |
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- | 0.4118 | 2.94 | 675 | 0.8105 | 0.4605 |
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- | 0.3642 | 3.05 | 700 | 0.8026 | 0.4409 |
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- | 0.2803 | 3.16 | 725 | 0.8131 | 0.4297 |
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- | 0.3533 | 3.27 | 750 | 0.7614 | 0.4346 |
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- | 0.2616 | 3.38 | 775 | 0.8177 | 0.4535 |
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- | 0.3203 | 3.49 | 800 | 0.7776 | 0.4409 |
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- | 0.2572 | 3.59 | 825 | 0.7438 | 0.4206 |
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- | 0.312 | 3.7 | 850 | 0.7454 | 0.4143 |
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- | 0.2338 | 3.81 | 875 | 0.7815 | 0.4192 |
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- | 0.2921 | 3.92 | 900 | 0.7109 | 0.4122 |
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- | 0.2568 | 4.03 | 925 | 0.7430 | 0.4157 |
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- | 0.1986 | 4.14 | 950 | 0.7301 | 0.4101 |
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- | 0.2569 | 4.25 | 975 | 0.7449 | 0.4150 |
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- | 0.1871 | 4.36 | 1000 | 0.7674 | 0.4108 |
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- | 0.2449 | 4.47 | 1025 | 0.7218 | 0.4080 |
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- | 0.1846 | 4.58 | 1050 | 0.7219 | 0.3933 |
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- | 0.2327 | 4.68 | 1075 | 0.7094 | 0.4080 |
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- | 0.1921 | 4.79 | 1100 | 0.6858 | 0.4031 |
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- | 0.2246 | 4.9 | 1125 | 0.6848 | 0.4059 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: Harveenchadha/vakyansh-wav2vec2-hindi-him-4200
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # hindi_wav2vec2_optimized
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+ This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-hindi-him-4200](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-hindi-him-4200) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4854
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+ - Wer: 0.3632
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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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+ | 2.1601 | 0.11 | 25 | 1.5548 | 0.4892 |
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+ | 2.8628 | 0.22 | 50 | 1.4072 | 0.6004 |
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+ | 1.5585 | 0.33 | 75 | 1.3488 | 0.5654 |
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+ | 2.8588 | 0.44 | 100 | 1.5733 | 0.5500 |
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+ | 1.3384 | 0.54 | 125 | 1.2629 | 0.5381 |
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+ | 1.7817 | 0.65 | 150 | 1.4159 | 0.5626 |
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+ | 1.124 | 0.76 | 175 | 1.1186 | 0.5003 |
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+ | 1.502 | 0.87 | 200 | 1.3352 | 0.5738 |
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+ | 1.0237 | 0.98 | 225 | 1.2497 | 0.6165 |
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+ | 0.9385 | 1.09 | 250 | 0.9858 | 0.5073 |
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+ | 1.5313 | 1.2 | 275 | 1.1366 | 0.5619 |
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+ | 0.9124 | 1.31 | 300 | 0.9704 | 0.4787 |
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+ | 0.649 | 1.42 | 325 | 1.1915 | 0.5458 |
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+ | 0.838 | 1.53 | 350 | 1.5229 | 0.5836 |
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+ | 0.6835 | 1.63 | 375 | 1.0692 | 0.5052 |
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+ | 0.823 | 1.74 | 400 | 0.9683 | 0.4640 |
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+ | 0.968 | 1.85 | 425 | 0.9629 | 0.4836 |
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+ | 0.8596 | 1.96 | 450 | 0.8242 | 0.4682 |
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+ | 0.6729 | 2.07 | 475 | 0.7999 | 0.4346 |
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+ | 0.6426 | 2.18 | 500 | 0.9678 | 0.4885 |
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+ | 0.7213 | 2.29 | 525 | 1.1779 | 0.5353 |
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+ | 0.4131 | 2.4 | 550 | 0.7007 | 0.4738 |
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+ | 0.4188 | 2.51 | 575 | 0.6085 | 0.4199 |
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+ | 0.3784 | 2.61 | 600 | 0.6526 | 0.4542 |
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+ | 0.4181 | 2.72 | 625 | 0.6716 | 0.4157 |
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+ | 0.3194 | 2.83 | 650 | 0.6058 | 0.4185 |
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+ | 0.3553 | 2.94 | 675 | 0.6023 | 0.4276 |
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+ | 0.3242 | 3.05 | 700 | 0.5864 | 0.4178 |
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+ | 0.2655 | 3.16 | 725 | 0.5705 | 0.3989 |
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+ | 0.3149 | 3.27 | 750 | 0.5275 | 0.3961 |
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+ | 0.2454 | 3.38 | 775 | 0.5401 | 0.3968 |
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+ | 0.2792 | 3.49 | 800 | 0.5303 | 0.3919 |
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+ | 0.2488 | 3.59 | 825 | 0.5459 | 0.4010 |
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+ | 0.3013 | 3.7 | 850 | 0.5180 | 0.3856 |
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+ | 0.2306 | 3.81 | 875 | 0.5179 | 0.3814 |
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+ | 0.2578 | 3.92 | 900 | 0.5168 | 0.3765 |
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+ | 0.2344 | 4.03 | 925 | 0.5212 | 0.3737 |
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+ | 0.2002 | 4.14 | 950 | 0.5026 | 0.3674 |
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+ | 0.2443 | 4.25 | 975 | 0.5045 | 0.3716 |
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+ | 0.1857 | 4.36 | 1000 | 0.5083 | 0.3751 |
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+ | 0.2158 | 4.47 | 1025 | 0.4941 | 0.3681 |
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+ | 0.1922 | 4.58 | 1050 | 0.4996 | 0.3723 |
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+ | 0.217 | 4.68 | 1075 | 0.4943 | 0.3695 |
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+ | 0.1888 | 4.79 | 1100 | 0.4849 | 0.3653 |
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+ | 0.1971 | 4.9 | 1125 | 0.4854 | 0.3632 |
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  ### Framework versions