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--- |
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language: |
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- ja |
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license: other |
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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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- Elite35P-Server/EliteVoiceProject |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Japanese Elite |
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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: Elite35P-Server/EliteVoiceProject youtube |
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type: Elite35P-Server/EliteVoiceProject |
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config: youtube |
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split: test |
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args: youtube |
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metrics: |
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- name: Wer |
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type: wer |
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value: 31.536388140161726 |
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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 Small Japanese Elite |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Elite35P-Server/EliteVoiceProject youtube dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1596 |
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- Wer: 31.5364 |
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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: 16 |
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- eval_batch_size: 8 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 10000 |
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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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| 0.0003 | 52.0 | 1000 | 0.8053 | 28.8410 | |
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| 0.0 | 105.0 | 2000 | 0.8636 | 28.5714 | |
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| 0.0 | 157.0 | 3000 | 0.9056 | 28.0323 | |
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| 0.0 | 210.0 | 4000 | 0.9414 | 28.8410 | |
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| 0.0 | 263.0 | 5000 | 0.9842 | 31.2668 | |
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| 0.0 | 315.0 | 6000 | 1.0223 | 31.2668 | |
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| 0.0 | 368.0 | 7000 | 1.0677 | 31.2668 | |
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| 0.0 | 421.0 | 8000 | 1.1079 | 31.2668 | |
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| 0.0 | 473.0 | 9000 | 1.1468 | 31.5364 | |
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| 0.0 | 526.0 | 10000 | 1.1596 | 31.5364 | |
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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 2.8.1.dev0 |
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- Tokenizers 0.13.2 |
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