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--- |
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library_name: transformers |
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language: |
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- my |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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datasets: |
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- chuuhtetnaing/myanmar-speech-dataset-openslr-80 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large V3 Turbo Burmese Finetune |
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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: Myanmar Speech Dataset (OpenSLR-80) |
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type: chuuhtetnaing/myanmar-speech-dataset-openslr-80 |
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args: 'config: my, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 47.10596616206589 |
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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 Turbo Burmese Finetune |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Myanmar Speech Dataset (OpenSLR-80) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1727 |
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- Wer: 47.1060 |
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- Cer: 15.6324 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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_ratio: 0.1 |
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- num_epochs: 20 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
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| 0.8922 | 1.0 | 143 | 0.4413 | 95.9484 | 48.4730 | |
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| 0.2576 | 2.0 | 286 | 0.1971 | 83.8379 | 26.9627 | |
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| 0.1481 | 3.0 | 429 | 0.1505 | 66.4292 | 22.9769 | |
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| 0.0996 | 4.0 | 572 | 0.1315 | 62.0214 | 20.5786 | |
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| 0.0697 | 5.0 | 715 | 0.1344 | 60.8638 | 20.5786 | |
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| 0.0507 | 6.0 | 858 | 0.1249 | 57.3464 | 19.3075 | |
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| 0.038 | 7.0 | 1001 | 0.1273 | 55.2538 | 18.4391 | |
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| 0.0279 | 8.0 | 1144 | 0.1257 | 54.4524 | 18.4908 | |
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| 0.02 | 9.0 | 1287 | 0.1374 | 53.3838 | 17.9559 | |
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| 0.0147 | 10.0 | 1430 | 0.1422 | 53.3393 | 17.9847 | |
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| 0.0101 | 11.0 | 1573 | 0.1530 | 53.8736 | 17.9674 | |
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| 0.0066 | 12.0 | 1716 | 0.1512 | 50.8905 | 16.8344 | |
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| 0.0043 | 13.0 | 1859 | 0.1526 | 49.5993 | 16.2708 | |
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| 0.0026 | 14.0 | 2002 | 0.1594 | 49.9110 | 16.4261 | |
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| 0.0017 | 15.0 | 2145 | 0.1612 | 49.0205 | 16.2248 | |
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| 0.0008 | 16.0 | 2288 | 0.1646 | 48.7088 | 15.9027 | |
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| 0.0003 | 17.0 | 2431 | 0.1676 | 47.8629 | 15.9429 | |
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| 0.0001 | 18.0 | 2574 | 0.1707 | 47.5512 | 15.6209 | |
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| 0.0001 | 19.0 | 2717 | 0.1721 | 47.3731 | 15.6439 | |
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| 0.0 | 20.0 | 2860 | 0.1727 | 47.1060 | 15.6324 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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