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--- |
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library_name: transformers |
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language: |
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- bem |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- BIG-C/BEMBA |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Bemba - Beijuka Bruno |
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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: BEMBA |
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type: BIG-C/BEMBA |
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args: 'config: bemba, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.6407617746274392 |
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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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# Whisper Small Bemba - Beijuka Bruno |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the BEMBA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3624 |
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- Wer: 0.6408 |
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- Cer: 0.1701 |
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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: 1e-05 |
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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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- 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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 2.6721 | 1.0 | 32 | 2.4561 | 1.5330 | 0.6440 | |
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| 2.2935 | 2.0 | 64 | 1.9492 | 0.9650 | 0.3391 | |
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| 1.7575 | 3.0 | 96 | 1.5668 | 0.8598 | 0.2686 | |
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| 1.4295 | 4.0 | 128 | 1.3788 | 0.7765 | 0.2352 | |
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| 1.1759 | 5.0 | 160 | 1.2559 | 0.7586 | 0.2371 | |
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| 0.9792 | 6.0 | 192 | 1.1833 | 0.7439 | 0.2093 | |
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| 0.8037 | 7.0 | 224 | 1.1540 | 0.6931 | 0.2193 | |
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| 0.6423 | 8.0 | 256 | 1.1380 | 0.6857 | 0.1988 | |
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| 0.462 | 9.0 | 288 | 1.1553 | 0.6905 | 0.2055 | |
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| 0.3141 | 10.0 | 320 | 1.1998 | 0.7169 | 0.2213 | |
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| 0.2089 | 11.0 | 352 | 1.2249 | 0.6661 | 0.1869 | |
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| 0.1359 | 12.0 | 384 | 1.2399 | 0.7071 | 0.2051 | |
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| 0.0831 | 13.0 | 416 | 1.2533 | 0.7148 | 0.2138 | |
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| 0.0553 | 14.0 | 448 | 1.2758 | 0.6553 | 0.1773 | |
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| 0.0334 | 15.0 | 480 | 1.3205 | 0.6406 | 0.1766 | |
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| 0.0286 | 16.0 | 512 | 1.2915 | 0.6486 | 0.1774 | |
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| 0.0248 | 17.0 | 544 | 1.3042 | 0.6628 | 0.1861 | |
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| 0.0177 | 18.0 | 576 | 1.3364 | 0.6628 | 0.1930 | |
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| 0.0131 | 19.0 | 608 | 1.3429 | 0.6505 | 0.1832 | |
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| 0.0116 | 20.0 | 640 | 1.3442 | 0.6763 | 0.2078 | |
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| 0.0105 | 21.0 | 672 | 1.3807 | 0.6548 | 0.1787 | |
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| 0.0056 | 22.0 | 704 | 1.3839 | 0.6480 | 0.1775 | |
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| 0.005 | 23.0 | 736 | 1.3965 | 0.6402 | 0.1775 | |
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| 0.0059 | 24.0 | 768 | 1.3936 | 0.6605 | 0.1941 | |
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| 0.0055 | 25.0 | 800 | 1.3850 | 0.6471 | 0.1871 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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