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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: 0.2619660819281792 |
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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: 0.2146 |
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- Model Preparation Time: 0.0203 |
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- Wer: 0.2620 |
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- Cer: 0.0482 |
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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: 4 |
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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: 16 |
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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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| 9.7791 | 1.0 | 546 | 0.2166 | 0.0203 | 0.3124 | 0.0531 | |
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| 0.9395 | 2.0 | 1092 | 0.2028 | 0.0203 | 0.2937 | 0.0494 | |
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| 0.8823 | 3.0 | 1638 | 0.1954 | 0.0203 | 0.2847 | 0.0479 | |
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| 0.8476 | 4.0 | 2184 | 0.1902 | 0.0203 | 0.2733 | 0.0460 | |
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| 0.8178 | 5.0 | 2730 | 0.1886 | 0.0203 | 0.2677 | 0.0451 | |
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| 0.7954 | 6.0 | 3276 | 0.1859 | 0.0203 | 0.2673 | 0.0443 | |
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| 0.7758 | 7.0 | 3822 | 0.1829 | 0.0203 | 0.2641 | 0.0440 | |
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| 0.7604 | 8.0 | 4368 | 0.1824 | 0.0203 | 0.2576 | 0.0430 | |
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| 0.746 | 9.0 | 4914 | 0.1821 | 0.0203 | 0.2678 | 0.0438 | |
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| 0.7375 | 10.0 | 5460 | 0.1802 | 0.0203 | 0.2609 | 0.0433 | |
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| 0.7223 | 11.0 | 6006 | 0.1800 | 0.0203 | 0.2572 | 0.0428 | |
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| 0.714 | 12.0 | 6552 | 0.1782 | 0.0203 | 0.2564 | 0.0426 | |
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| 0.7007 | 13.0 | 7098 | 0.1753 | 0.0203 | 0.2552 | 0.0421 | |
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| 0.6923 | 14.0 | 7644 | 0.1764 | 0.0203 | 0.2560 | 0.0421 | |
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| 0.6842 | 15.0 | 8190 | 0.1769 | 0.0203 | 0.2563 | 0.0422 | |
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| 0.6742 | 16.0 | 8736 | 0.1733 | 0.0203 | 0.2483 | 0.0410 | |
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| 0.6655 | 17.0 | 9282 | 0.1767 | 0.0203 | 0.2506 | 0.0415 | |
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| 0.6594 | 18.0 | 9828 | 0.1750 | 0.0203 | 0.2503 | 0.0412 | |
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| 0.651 | 19.0 | 10374 | 0.1733 | 0.0203 | 0.2513 | 0.0413 | |
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| 0.6435 | 20.0 | 10920 | 0.1767 | 0.0203 | 0.2458 | 0.0410 | |
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| 0.637 | 21.0 | 11466 | 0.1773 | 0.0203 | 0.2449 | 0.0407 | |
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| 0.6306 | 22.0 | 12012 | 0.1750 | 0.0203 | 0.2488 | 0.0411 | |
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| 0.6216 | 23.0 | 12558 | 0.1738 | 0.0203 | 0.2507 | 0.0412 | |
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| 0.6174 | 24.0 | 13104 | 0.1788 | 0.0203 | 0.2450 | 0.0407 | |
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| 0.6093 | 25.0 | 13650 | 0.1802 | 0.0203 | 0.2479 | 0.0408 | |
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| 0.6033 | 26.0 | 14196 | 0.1801 | 0.0203 | 0.2463 | 0.0407 | |
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| 0.5932 | 27.0 | 14742 | 0.1793 | 0.0203 | 0.2462 | 0.0407 | |
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| 0.5885 | 28.0 | 15288 | 0.1780 | 0.0203 | 0.2465 | 0.0407 | |
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| 0.5823 | 29.0 | 15834 | 0.1802 | 0.0203 | 0.2465 | 0.0404 | |
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| 0.5749 | 30.0 | 16380 | 0.1794 | 0.0203 | 0.2465 | 0.0407 | |
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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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