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--- |
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language: |
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- zh |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Chinese-Mandarin |
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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_16_0 zh-CN |
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type: mozilla-foundation/common_voice_16_0 |
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config: zh-CN |
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split: test |
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args: zh-CN |
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metrics: |
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- name: Wer |
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type: wer |
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value: 89.13440626359287 |
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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 Base Chinese-Mandarin |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 zh-CN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5263 |
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- Wer: 89.1344 |
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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-07 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: 10000 |
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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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| 0.9769 | 1.02 | 500 | 0.6812 | 94.6411 | |
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| 0.8022 | 3.0 | 1000 | 0.6262 | 92.5794 | |
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| 0.9109 | 4.02 | 1500 | 0.6009 | 92.6229 | |
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| 0.7132 | 6.0 | 2000 | 0.5845 | 92.3967 | |
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| 0.8416 | 7.02 | 2500 | 0.5725 | 91.7616 | |
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| 0.6527 | 9.0 | 3000 | 0.5636 | 91.4659 | |
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| 0.812 | 10.02 | 3500 | 0.5561 | 90.8917 | |
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| 0.6584 | 12.0 | 4000 | 0.5504 | 90.7960 | |
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| 0.7825 | 13.02 | 4500 | 0.5455 | 90.4045 | |
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| 0.6174 | 15.0 | 5000 | 0.5416 | 90.0565 | |
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| 0.7925 | 16.02 | 5500 | 0.5381 | 90.0217 | |
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| 0.5983 | 18.0 | 6000 | 0.5355 | 89.7695 | |
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| 0.741 | 19.02 | 6500 | 0.5331 | 89.7086 | |
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| 0.5831 | 21.0 | 7000 | 0.5312 | 89.4998 | |
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| 0.7414 | 22.02 | 7500 | 0.5296 | 89.5259 | |
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| 0.5902 | 24.0 | 8000 | 0.5284 | 89.3084 | |
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| 0.7242 | 25.02 | 8500 | 0.5275 | 89.4041 | |
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| 0.5815 | 27.0 | 9000 | 0.5268 | 89.1518 | |
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| 0.717 | 28.02 | 9500 | 0.5265 | 89.2562 | |
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| 0.5887 | 30.0 | 10000 | 0.5263 | 89.1344 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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