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--- |
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license: apache-2.0 |
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base_model: Wellyowo/whisper-tiny-zh-tw |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-zh-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: common_voice_13_0 |
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type: common_voice_13_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: 59.22330097087378 |
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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-zh-tw |
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This model is a fine-tuned version of [Wellyowo/whisper-tiny-zh-tw](https://huggingface.co/Wellyowo/whisper-tiny-zh-tw) on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5683 |
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- Wer Ortho: 60.0 |
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- Wer: 59.2233 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 4000 |
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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 Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| |
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| 0.1844 | 0.69 | 500 | 0.5523 | 64.0 | 65.0485 | |
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| 0.1105 | 1.38 | 1000 | 0.5425 | 65.0 | 64.0777 | |
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| 0.0475 | 2.06 | 1500 | 0.5324 | 63.0 | 64.0777 | |
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| 0.0687 | 2.75 | 2000 | 0.5128 | 62.0 | 61.1650 | |
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| 0.0371 | 3.44 | 2500 | 0.5496 | 64.0 | 64.0777 | |
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| 0.0181 | 4.13 | 3000 | 0.5339 | 62.0 | 63.1068 | |
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| 0.0202 | 4.82 | 3500 | 0.5474 | 65.0 | 64.0777 | |
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| 0.011 | 5.51 | 4000 | 0.5683 | 60.0 | 59.2233 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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