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--- |
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language: |
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- yue |
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license: apache-2.0 |
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base_model: poppysmickarlili/whisper-small-cantonese_07-05-2024-2200 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- poppysmickarlili/common_voice_yue |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Cantanese |
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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: poppysmickarlili/common_voice_yue |
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type: poppysmickarlili/common_voice_yue |
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args: 'config: yue, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.017123287671232876 |
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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 Cantanese |
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This model is a fine-tuned version of [poppysmickarlili/whisper-small-cantonese_07-05-2024-2200](https://huggingface.co/poppysmickarlili/whisper-small-cantonese_07-05-2024-2200) on the poppysmickarlili/common_voice_yue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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- Wer: 0.0171 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- training_steps: 4000 |
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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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| 0.0039 | 2.7816 | 1000 | 0.0040 | 1.3699 | |
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| 0.0006 | 5.5633 | 2000 | 0.0001 | 0.0514 | |
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| 0.0001 | 8.3449 | 3000 | 0.0001 | 0.0171 | |
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| 0.0 | 11.1377 | 4000 | 0.0000 | 0.0171 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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