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--- |
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library_name: transformers |
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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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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-finetuned-nan-tw-v3-torbo-20-epoch |
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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: common_voice_17_0 |
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type: common_voice_17_0 |
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config: nan-tw |
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split: test |
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args: nan-tw |
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metrics: |
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- name: Wer |
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type: wer |
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value: 100.0 |
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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-finetuned-nan-tw-v3-torbo-20-epoch |
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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 common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2611 |
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- Wer: 100.0 |
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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: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.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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- 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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| 0.2238 | 1.0616 | 500 | 0.2174 | 100.0 | |
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| 0.1871 | 2.1233 | 1000 | 0.2099 | 100.0 | |
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| 0.1606 | 3.1849 | 1500 | 0.2050 | 100.0 | |
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| 0.1315 | 4.2465 | 2000 | 0.2134 | 100.0 | |
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| 0.1087 | 5.3082 | 2500 | 0.2247 | 100.0 | |
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| 0.0969 | 6.3698 | 3000 | 0.2269 | 100.0 | |
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| 0.0851 | 7.4315 | 3500 | 0.2381 | 100.0 | |
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| 0.0793 | 8.4931 | 4000 | 0.2412 | 100.0 | |
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| 0.0737 | 9.5547 | 4500 | 0.2406 | 100.0 | |
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| 0.07 | 10.6164 | 5000 | 0.2452 | 99.9569 | |
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| 0.0669 | 11.6780 | 5500 | 0.2435 | 100.0 | |
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| 0.0623 | 12.7396 | 6000 | 0.2447 | 100.0 | |
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| 0.0605 | 13.8013 | 6500 | 0.2490 | 100.0 | |
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| 0.0563 | 14.8629 | 7000 | 0.2524 | 99.9569 | |
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| 0.0525 | 15.9245 | 7500 | 0.2536 | 100.0 | |
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| 0.0485 | 16.9862 | 8000 | 0.2554 | 100.0 | |
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| 0.0435 | 18.0468 | 8500 | 0.2591 | 100.0 | |
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| 0.0386 | 19.1084 | 9000 | 0.2611 | 100.0 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.1 |
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- Tokenizers 0.21.0 |
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