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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-large-v3-myanmar |
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results: [] |
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datasets: |
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- chuuhtetnaing/myanmar-speech-dataset-openslr-80 |
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language: |
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- my |
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pipeline_tag: automatic-speech-recognition |
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library_name: transformers |
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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-large-v3-myanmar |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the [chuuhtetnaing/myanmar-speech-dataset-openslr-80](https://huggingface.co/datasets/chuuhtetnaing/myanmar-speech-dataset-openslr-80) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1752 |
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- Wer: 54.8976 |
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## Usage |
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```python |
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from datasets import Audio, load_dataset |
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from transformers import pipeline |
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# Load a sample audio |
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dataset = load_dataset("chuuhtetnaing/myanmar-speech-dataset-openslr-80") |
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dataset = dataset.cast_column("audio", Audio(sampling_rate=16000)) |
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test_dataset = dataset['test'] |
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input_speech = test_dataset[42]['audio'] |
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pipe = pipeline(model='chuuhtetnaing/whisper-large-v3-myanmar') |
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output = pipe(input_speech, generate_kwargs={"language": "myanmar", "task": "transcribe"}) |
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print(output['text']) # αα»α ααΌααΊα ααΎα¬ ααα¬αααΊ αα±α¬α· α
α¬αα±αΈαα½α² ααα― ααααΊααα« α
α
αΊαααΊ |
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``` |
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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: 20 |
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- eval_batch_size: 20 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 60 |
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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: 200 |
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- num_epochs: 30 |
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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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| 0.9771 | 1.0 | 42 | 0.7598 | 100.0 | |
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| 0.3477 | 2.0 | 84 | 0.2140 | 89.8931 | |
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| 0.2244 | 3.0 | 126 | 0.1816 | 79.0294 | |
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| 0.1287 | 4.0 | 168 | 0.1510 | 71.9947 | |
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| 0.1029 | 5.0 | 210 | 0.1575 | 77.8718 | |
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| 0.0797 | 6.0 | 252 | 0.1315 | 70.5254 | |
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| 0.0511 | 7.0 | 294 | 0.1143 | 70.5699 | |
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| 0.03 | 8.0 | 336 | 0.1154 | 68.1656 | |
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| 0.0211 | 9.0 | 378 | 0.1289 | 69.1897 | |
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| 0.0151 | 10.0 | 420 | 0.1318 | 66.7854 | |
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| 0.0113 | 11.0 | 462 | 0.1478 | 69.1451 | |
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| 0.0079 | 12.0 | 504 | 0.1484 | 66.2066 | |
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| 0.0053 | 13.0 | 546 | 0.1389 | 65.0935 | |
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| 0.0031 | 14.0 | 588 | 0.1479 | 64.3811 | |
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| 0.0014 | 15.0 | 630 | 0.1611 | 64.8264 | |
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| 0.001 | 16.0 | 672 | 0.1627 | 63.3571 | |
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| 0.0012 | 17.0 | 714 | 0.1546 | 65.0045 | |
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| 0.0006 | 18.0 | 756 | 0.1566 | 64.5147 | |
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| 0.0006 | 20.0 | 760 | 0.1581 | 64.6928 | |
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| 0.0002 | 21.0 | 798 | 0.1621 | 63.9804 | |
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| 0.0003 | 22.0 | 836 | 0.1664 | 60.8638 | |
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| 0.0002 | 23.0 | 874 | 0.1663 | 58.5040 | |
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| 0.0 | 24.0 | 912 | 0.1699 | 55.8326 | |
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| 0.0 | 25.0 | 950 | 0.1715 | 55.0312 | |
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| 0.0 | 26.0 | 988 | 0.1730 | 54.9866 | |
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| 0.0 | 27.0 | 1026 | 0.1740 | 54.8976 | |
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| 0.0 | 28.0 | 1064 | 0.1747 | 54.8976 | |
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| 0.0 | 29.0 | 1102 | 0.1751 | 54.8976 | |
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| 0.0 | 30.0 | 1140 | 0.1752 | 54.8976 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.15.1 |
