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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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tags: |
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- whisper |
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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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- wer |
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model-index: |
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- name: Whisper Small Chinese - Bingcheng Hu |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: zh-CN |
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split: test[:1%] |
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args: 'config: chinese, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 226.41509433962264 |
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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 Chinese - Bingcheng Hu |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7064 |
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- Wer: 226.4151 |
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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: 5 |
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- training_steps: 400 |
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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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| 0.8417 | 1.08 | 20 | 1.4964 | 598.1132 | |
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| 1.2552 | 2.16 | 40 | 1.4901 | 367.9245 | |
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| 0.8195 | 3.24 | 60 | 1.4953 | 391.5094 | |
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| 0.6174 | 4.32 | 80 | 1.5091 | 475.4717 | |
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| 0.4594 | 5.41 | 100 | 1.5318 | 520.7547 | |
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| 0.489 | 6.49 | 120 | 1.5558 | 863.2075 | |
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| 0.4673 | 7.57 | 140 | 1.5719 | 663.2075 | |
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| 0.3976 | 8.65 | 160 | 1.5962 | 682.0755 | |
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| 0.3518 | 9.73 | 180 | 1.6160 | 623.5849 | |
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| 0.3043 | 10.81 | 200 | 1.6219 | 620.7547 | |
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| 0.2524 | 11.89 | 220 | 1.6505 | 598.1132 | |
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| 0.259 | 12.97 | 240 | 1.6543 | 329.2453 | |
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| 0.1696 | 14.05 | 260 | 1.6678 | 333.0189 | |
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| 0.1188 | 15.14 | 280 | 1.6746 | 329.2453 | |
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| 0.1366 | 16.22 | 300 | 1.6852 | 428.3019 | |
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| 0.1165 | 17.3 | 320 | 1.6979 | 262.2642 | |
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| 0.1062 | 18.38 | 340 | 1.7021 | 338.6792 | |
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| 0.0882 | 19.46 | 360 | 1.7047 | 313.2075 | |
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| 0.0891 | 20.54 | 380 | 1.7054 | 302.8302 | |
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| 0.0676 | 21.62 | 400 | 1.7064 | 226.4151 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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