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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-event |
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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 Tiny Chinese (Taiwanese 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_11_0 zh-TW |
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type: mozilla-foundation/common_voice_11_0 |
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config: zh-TW |
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split: test |
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args: zh-TW |
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metrics: |
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- name: Wer |
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type: wer |
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value: 68.84339815762537 |
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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 Tiny Chinese (Taiwanese Mandarin) |
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This model is a fine-tuned version of [xmzhu/whisper-tiny-zh](https://huggingface.co./xmzhu/whisper-tiny-zh) on the mozilla-foundation/common_voice_11_0 zh-TW dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4879 |
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- Wer: 68.8434 |
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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: 64 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.1221 | 6.02 | 1000 | 0.4879 | 68.8434 | |
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| 0.0119 | 13.02 | 2000 | 0.5567 | 70.2354 | |
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| 0.004 | 20.01 | 3000 | 0.5890 | 70.6244 | |
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| 0.0027 | 27.0 | 4000 | 0.6128 | 72.4053 | |
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| 0.0021 | 33.02 | 5000 | 0.6177 | 71.9140 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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