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README.md
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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 large-v2 nan-tw
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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 nan-tw
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type: mozilla-foundation/common_voice_11_0
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config: nan-tw
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split: train
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args: nan-tw
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metrics:
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- name: Wer
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type: wer
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value: 118.50381679389312
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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 nan-tw
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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 nan-tw dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.2129
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- Wer: 118.5038
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- Cer: 123.4531
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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: 2
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- eval_batch_size: 2
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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| 3.5696 | 1.04 | 1000 | 3.4190 | 96.8550 | 96.8910 |
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| 3.1453 | 2.08 | 2000 | 3.2383 | 98.9313 | 98.9436 |
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| 3.0722 | 3.13 | 3000 | 3.2043 | 129.0687 | 158.5270 |
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| 2.8327 | 5.01 | 4000 | 3.2258 | 327.9084 | 333.0516 |
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| 2.6468 | 6.05 | 5000 | 3.2129 | 118.5038 | 123.4531 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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