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--- |
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library_name: transformers |
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language: |
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- sn |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- DigitalUmuganda_Afrivoice/Shona |
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metrics: |
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- wer |
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model-index: |
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- name: facebook/mms-1b-all |
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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: DigitalUmuganda |
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type: DigitalUmuganda_Afrivoice/Shona |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.276446863307255 |
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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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# facebook/mms-1b-all |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the DigitalUmuganda dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2338 |
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- Model Preparation Time: 0.0115 |
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- Wer: 0.2764 |
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- Cer: 0.0510 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 150 |
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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 | Model Preparation Time | Wer | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:| |
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| 36.4063 | 0.9954 | 109 | 5.1803 | 0.0115 | 1.0 | 0.9463 | |
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| 19.0038 | 2.0 | 219 | 4.0762 | 0.0115 | 1.0696 | 0.7878 | |
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| 14.6479 | 2.9954 | 328 | 3.2461 | 0.0115 | 0.9999 | 0.9420 | |
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| 12.4828 | 4.0 | 438 | 2.8917 | 0.0115 | 1.0 | 0.8262 | |
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| 11.4667 | 4.9954 | 547 | 2.7706 | 0.0115 | 1.0006 | 0.7752 | |
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| 10.9805 | 6.0 | 657 | 2.6967 | 0.0115 | 1.0007 | 0.7594 | |
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| 10.6692 | 6.9954 | 766 | 2.4726 | 0.0115 | 1.0 | 0.7709 | |
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| 2.4538 | 8.0 | 876 | 0.2426 | 0.0115 | 0.3420 | 0.0586 | |
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| 1.0883 | 8.9954 | 985 | 0.2242 | 0.0115 | 0.3166 | 0.0541 | |
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| 1.0062 | 10.0 | 1095 | 0.2119 | 0.0115 | 0.3104 | 0.0523 | |
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| 0.9739 | 10.9954 | 1204 | 0.2072 | 0.0115 | 0.3081 | 0.0510 | |
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| 0.934 | 12.0 | 1314 | 0.2035 | 0.0115 | 0.2992 | 0.0498 | |
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| 0.9141 | 12.9954 | 1423 | 0.2000 | 0.0115 | 0.2934 | 0.0492 | |
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| 0.8906 | 14.0 | 1533 | 0.1973 | 0.0115 | 0.2896 | 0.0485 | |
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| 0.8799 | 14.9954 | 1642 | 0.1958 | 0.0115 | 0.2883 | 0.0478 | |
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| 0.8563 | 16.0 | 1752 | 0.1952 | 0.0115 | 0.2843 | 0.0475 | |
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| 0.8487 | 16.9954 | 1861 | 0.1929 | 0.0115 | 0.2841 | 0.0469 | |
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| 0.8292 | 18.0 | 1971 | 0.1909 | 0.0115 | 0.2799 | 0.0466 | |
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| 0.8203 | 18.9954 | 2080 | 0.1892 | 0.0115 | 0.2815 | 0.0468 | |
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| 0.8039 | 20.0 | 2190 | 0.1897 | 0.0115 | 0.2789 | 0.0460 | |
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| 0.8014 | 20.9954 | 2299 | 0.1899 | 0.0115 | 0.2852 | 0.0470 | |
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| 0.7822 | 22.0 | 2409 | 0.1883 | 0.0115 | 0.2761 | 0.0457 | |
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| 0.783 | 22.9954 | 2518 | 0.1860 | 0.0115 | 0.2757 | 0.0456 | |
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| 0.765 | 24.0 | 2628 | 0.1869 | 0.0115 | 0.2728 | 0.0451 | |
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| 0.7608 | 24.9954 | 2737 | 0.1844 | 0.0115 | 0.2701 | 0.0448 | |
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| 0.7494 | 26.0 | 2847 | 0.1851 | 0.0115 | 0.2704 | 0.0444 | |
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| 0.7414 | 26.9954 | 2956 | 0.1841 | 0.0115 | 0.2713 | 0.0450 | |
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| 0.73 | 28.0 | 3066 | 0.1855 | 0.0115 | 0.2672 | 0.0443 | |
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| 0.7282 | 28.9954 | 3175 | 0.1859 | 0.0115 | 0.2706 | 0.0442 | |
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| 0.7164 | 30.0 | 3285 | 0.1837 | 0.0115 | 0.2683 | 0.0441 | |
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| 0.7145 | 30.9954 | 3394 | 0.1835 | 0.0115 | 0.2743 | 0.0447 | |
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| 0.7027 | 32.0 | 3504 | 0.1855 | 0.0115 | 0.2739 | 0.0443 | |
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| 0.6973 | 32.9954 | 3613 | 0.1843 | 0.0115 | 0.2674 | 0.0438 | |
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| 0.6869 | 34.0 | 3723 | 0.1832 | 0.0115 | 0.2699 | 0.0440 | |
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| 0.683 | 34.9954 | 3832 | 0.1834 | 0.0115 | 0.2722 | 0.0441 | |
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| 0.6677 | 36.0 | 3942 | 0.1818 | 0.0115 | 0.2684 | 0.0439 | |
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| 0.67 | 36.9954 | 4051 | 0.1825 | 0.0115 | 0.2631 | 0.0435 | |
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| 0.6577 | 38.0 | 4161 | 0.1850 | 0.0115 | 0.2744 | 0.0442 | |
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| 0.6545 | 38.9954 | 4270 | 0.1819 | 0.0115 | 0.2694 | 0.0438 | |
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| 0.6412 | 40.0 | 4380 | 0.1860 | 0.0115 | 0.2711 | 0.0438 | |
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| 0.6455 | 40.9954 | 4489 | 0.1837 | 0.0115 | 0.2635 | 0.0431 | |
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| 0.6259 | 42.0 | 4599 | 0.1841 | 0.0115 | 0.2638 | 0.0430 | |
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| 0.6344 | 42.9954 | 4708 | 0.1855 | 0.0115 | 0.2671 | 0.0434 | |
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| 0.619 | 44.0 | 4818 | 0.1840 | 0.0115 | 0.2627 | 0.0428 | |
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| 0.6137 | 44.9954 | 4927 | 0.1857 | 0.0115 | 0.2596 | 0.0426 | |
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| 0.6058 | 46.0 | 5037 | 0.1827 | 0.0115 | 0.2656 | 0.0430 | |
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| 0.6009 | 46.9954 | 5146 | 0.1851 | 0.0115 | 0.2654 | 0.0429 | |
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| 0.5885 | 48.0 | 5256 | 0.1837 | 0.0115 | 0.2619 | 0.0423 | |
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| 0.5892 | 48.9954 | 5365 | 0.1851 | 0.0115 | 0.2681 | 0.0429 | |
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| 0.5741 | 50.0 | 5475 | 0.1869 | 0.0115 | 0.2610 | 0.0427 | |
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| 0.5812 | 50.9954 | 5584 | 0.1861 | 0.0115 | 0.2600 | 0.0426 | |
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| 0.5653 | 52.0 | 5694 | 0.1847 | 0.0115 | 0.2651 | 0.0431 | |
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| 0.5604 | 52.9954 | 5803 | 0.1886 | 0.0115 | 0.2641 | 0.0428 | |
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| 0.5532 | 54.0 | 5913 | 0.1891 | 0.0115 | 0.2638 | 0.0428 | |
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| 0.5533 | 54.9954 | 6022 | 0.1894 | 0.0115 | 0.2602 | 0.0421 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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