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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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metrics:
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- wer
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model-index:
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- name:
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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:
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type:
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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:
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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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#
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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## Model description
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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:
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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:
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- training_steps: 1000
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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### Framework versions
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- 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: openai/whisper-small
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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: 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: 32.594792142530835
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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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# openai/whisper-small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.3250
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- Wer: 32.5948
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## Model description
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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: 800
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- training_steps: 1000
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.3465 | 1.05 | 200 | 0.3499 | 41.9324 |
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| 0.2137 | 2.1 | 400 | 0.2953 | 36.2951 |
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| 0.1255 | 4.01 | 600 | 0.2927 | 33.7232 |
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| 0.0509 | 5.06 | 800 | 0.3149 | 34.0566 |
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| 0.0164 | 6.11 | 1000 | 0.3250 | 32.5948 |
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### Framework versions
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