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--- |
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language: |
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- dv |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- dv |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- model_for_talk |
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- mozilla-foundation/common_voice_8_0 |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: XLS-R-300M - Dhivehi |
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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: Common Voice 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: dv |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 21.31 |
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- name: Test CER |
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type: cer |
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value: 3.82 |
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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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# xls-r-300m-dv |
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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 common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2855 |
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- Wer: 0.2665 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 500 |
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- num_epochs: 50 |
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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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| 4.3386 | 0.66 | 400 | 1.1411 | 0.9432 | |
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| 0.6543 | 1.33 | 800 | 0.5099 | 0.6749 | |
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| 0.4646 | 1.99 | 1200 | 0.4133 | 0.5968 | |
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| 0.3748 | 2.65 | 1600 | 0.3534 | 0.5515 | |
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| 0.3323 | 3.32 | 2000 | 0.3635 | 0.5527 | |
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| 0.3269 | 3.98 | 2400 | 0.3587 | 0.5423 | |
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| 0.2984 | 4.64 | 2800 | 0.3340 | 0.5073 | |
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| 0.2841 | 5.31 | 3200 | 0.3279 | 0.5004 | |
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| 0.2664 | 5.97 | 3600 | 0.3114 | 0.4845 | |
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| 0.2397 | 6.63 | 4000 | 0.3174 | 0.4920 | |
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| 0.2332 | 7.3 | 4400 | 0.3110 | 0.4911 | |
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| 0.2304 | 7.96 | 4800 | 0.3123 | 0.4785 | |
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| 0.2134 | 8.62 | 5200 | 0.2984 | 0.4557 | |
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| 0.2066 | 9.29 | 5600 | 0.3013 | 0.4723 | |
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| 0.1951 | 9.95 | 6000 | 0.2934 | 0.4487 | |
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| 0.1806 | 10.61 | 6400 | 0.2802 | 0.4547 | |
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| 0.1727 | 11.28 | 6800 | 0.2842 | 0.4333 | |
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| 0.1666 | 11.94 | 7200 | 0.2873 | 0.4272 | |
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| 0.1562 | 12.6 | 7600 | 0.3042 | 0.4373 | |
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| 0.1483 | 13.27 | 8000 | 0.3122 | 0.4313 | |
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| 0.1465 | 13.93 | 8400 | 0.2760 | 0.4226 | |
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| 0.1335 | 14.59 | 8800 | 0.3112 | 0.4243 | |
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| 0.1293 | 15.26 | 9200 | 0.3002 | 0.4133 | |
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| 0.1264 | 15.92 | 9600 | 0.2985 | 0.4145 | |
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| 0.1179 | 16.58 | 10000 | 0.2925 | 0.4012 | |
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| 0.1171 | 17.25 | 10400 | 0.3127 | 0.4012 | |
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| 0.1141 | 17.91 | 10800 | 0.2980 | 0.3908 | |
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| 0.108 | 18.57 | 11200 | 0.3108 | 0.3951 | |
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| 0.1045 | 19.24 | 11600 | 0.3269 | 0.3908 | |
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| 0.1047 | 19.9 | 12000 | 0.2998 | 0.3868 | |
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| 0.0937 | 20.56 | 12400 | 0.2918 | 0.3875 | |
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| 0.0949 | 21.23 | 12800 | 0.2906 | 0.3657 | |
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| 0.0879 | 21.89 | 13200 | 0.2974 | 0.3731 | |
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| 0.0854 | 22.55 | 13600 | 0.2943 | 0.3711 | |
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| 0.0851 | 23.22 | 14000 | 0.2919 | 0.3580 | |
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| 0.0789 | 23.88 | 14400 | 0.2983 | 0.3560 | |
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| 0.0796 | 24.54 | 14800 | 0.3131 | 0.3544 | |
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| 0.0761 | 25.21 | 15200 | 0.2996 | 0.3616 | |
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| 0.0755 | 25.87 | 15600 | 0.2972 | 0.3506 | |
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| 0.0726 | 26.53 | 16000 | 0.2902 | 0.3474 | |
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| 0.0707 | 27.2 | 16400 | 0.3083 | 0.3480 | |
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| 0.0669 | 27.86 | 16800 | 0.3035 | 0.3330 | |
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| 0.0637 | 28.52 | 17200 | 0.2963 | 0.3370 | |
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| 0.0596 | 29.19 | 17600 | 0.2830 | 0.3326 | |
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| 0.0583 | 29.85 | 18000 | 0.2969 | 0.3287 | |
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| 0.0566 | 30.51 | 18400 | 0.3002 | 0.3480 | |
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| 0.0574 | 31.18 | 18800 | 0.2916 | 0.3296 | |
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| 0.0536 | 31.84 | 19200 | 0.2933 | 0.3225 | |
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| 0.0548 | 32.5 | 19600 | 0.2900 | 0.3179 | |
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| 0.0506 | 33.17 | 20000 | 0.3073 | 0.3225 | |
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| 0.0511 | 33.83 | 20400 | 0.2925 | 0.3275 | |
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| 0.0483 | 34.49 | 20800 | 0.2919 | 0.3245 | |
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| 0.0456 | 35.16 | 21200 | 0.2859 | 0.3105 | |
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| 0.0445 | 35.82 | 21600 | 0.2864 | 0.3080 | |
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| 0.0437 | 36.48 | 22000 | 0.2989 | 0.3084 | |
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| 0.04 | 37.15 | 22400 | 0.2887 | 0.3060 | |
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| 0.0406 | 37.81 | 22800 | 0.2870 | 0.3013 | |
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| 0.0397 | 38.47 | 23200 | 0.2793 | 0.3020 | |
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| 0.0383 | 39.14 | 23600 | 0.2955 | 0.2943 | |
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| 0.0345 | 39.8 | 24000 | 0.2813 | 0.2905 | |
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| 0.0331 | 40.46 | 24400 | 0.2845 | 0.2845 | |
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| 0.0338 | 41.13 | 24800 | 0.2832 | 0.2925 | |
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| 0.0333 | 41.79 | 25200 | 0.2889 | 0.2849 | |
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| 0.0325 | 42.45 | 25600 | 0.2808 | 0.2847 | |
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| 0.0314 | 43.12 | 26000 | 0.2867 | 0.2801 | |
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| 0.0288 | 43.78 | 26400 | 0.2865 | 0.2834 | |
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| 0.0291 | 44.44 | 26800 | 0.2863 | 0.2806 | |
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| 0.0269 | 45.11 | 27200 | 0.2941 | 0.2736 | |
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| 0.0275 | 45.77 | 27600 | 0.2897 | 0.2736 | |
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| 0.0271 | 46.43 | 28000 | 0.2857 | 0.2695 | |
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| 0.0251 | 47.1 | 28400 | 0.2881 | 0.2702 | |
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| 0.0243 | 47.76 | 28800 | 0.2901 | 0.2684 | |
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| 0.0244 | 48.42 | 29200 | 0.2849 | 0.2679 | |
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| 0.0232 | 49.09 | 29600 | 0.2849 | 0.2677 | |
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| 0.0224 | 49.75 | 30000 | 0.2855 | 0.2665 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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