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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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tags: |
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- whisper-event |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- cer |
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model-index: |
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- name: Whisper Large V2 Cantonese |
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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: mozilla-foundation/common_voice_11_0 |
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type: mozilla-foundation/common_voice_11_0 |
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split: test |
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config: yue |
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metrics: |
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- name: Cer |
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type: cer |
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value: 6.7274 |
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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 V2 Cantonese |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 yue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2807 |
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- Cer: 6.7274 |
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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: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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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: 5000 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.0032 | 13.01 | 1000 | 0.2318 | 6.8569 | |
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| 0.002 | 26.01 | 2000 | 0.2404 | 7.1524 | |
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| 0.0001 | 39.02 | 3000 | 0.2807 | 6.7274 | |
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| 0.0001 | 53.01 | 4000 | 0.2912 | 6.7517 | |
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| 0.0 | 66.01 | 5000 | 0.2957 | 6.7638 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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