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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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metrics: |
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- wer |
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model-index: |
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- name: wavlm-base-plus_zh_tw_ver3 |
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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 |
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type: common_voice |
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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: 1.0 |
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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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# wavlm-base-plus_zh_tw_ver3 |
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This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 11.5929 |
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- Wer: 1.0 |
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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: 7.5e-05 |
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- train_batch_size: 32 |
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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: 2000 |
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- num_epochs: 6.0 |
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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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| 82.628 | 2.5 | 500 | 79.5587 | 1.0 | |
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| 17.5635 | 5.0 | 1000 | 11.5929 | 1.0 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 1.12.0+cu102 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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