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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: 55.78806767586821 |
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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: 0.2310 |
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- Wer: 55.7881 |
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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: 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: 0.2 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.7755 | 1.0 | 143 | 0.3657 | 92.8317 | |
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| 0.2954 | 2.0 | 286 | 0.2669 | 85.6189 | |
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| 0.2483 | 3.0 | 429 | 0.2830 | 82.7248 | |
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| 0.2332 | 4.0 | 572 | 0.2922 | 83.3927 | |
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| 0.204 | 5.0 | 715 | 0.2338 | 78.8068 | |
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| 0.1612 | 6.0 | 858 | 0.1876 | 74.8442 | |
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| 0.1203 | 7.0 | 1001 | 0.1940 | 72.1728 | |
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| 0.0919 | 8.0 | 1144 | 0.1639 | 65.8504 | |
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| 0.0663 | 9.0 | 1287 | 0.1610 | 62.5557 | |
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| 0.0461 | 10.0 | 1430 | 0.1633 | 63.2235 | |
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| 0.0336 | 11.0 | 1573 | 0.1830 | 62.8228 | |
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| 0.0238 | 12.0 | 1716 | 0.1777 | 60.5521 | |
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| 0.0153 | 13.0 | 1859 | 0.1783 | 59.4835 | |
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| 0.0099 | 14.0 | 2002 | 0.1945 | 58.2369 | |
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| 0.0066 | 15.0 | 2145 | 0.2002 | 57.1683 | |
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| 0.003 | 16.0 | 2288 | 0.2148 | 57.1683 | |
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| 0.0015 | 17.0 | 2431 | 0.2241 | 55.9662 | |
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| 0.0006 | 18.0 | 2574 | 0.2286 | 56.2778 | |
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| 0.0003 | 19.0 | 2717 | 0.2296 | 55.8771 | |
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| 0.0001 | 20.0 | 2860 | 0.2310 | 55.7881 | |
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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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