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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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base_model: openai/whisper-base |
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model-index: |
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- name: Whisper Base Japanese Elite |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Elite35P-Server/EliteVoiceProject twitter |
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type: Elite35P-Server/EliteVoiceProject |
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config: twitter |
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split: test |
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args: twitter |
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metrics: |
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- type: wer |
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value: 17.073170731707318 |
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name: Wer |
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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 Base Japanese Elite |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Elite35P-Server/EliteVoiceProject twitter dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4385 |
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- Wer: 17.0732 |
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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: 32 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 200 |
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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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| 0.0002 | 111.0 | 1000 | 0.2155 | 9.7561 | |
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| 0.0001 | 222.0 | 2000 | 0.2448 | 12.1951 | |
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| 0.0 | 333.0 | 3000 | 0.2674 | 13.4146 | |
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| 0.0 | 444.0 | 4000 | 0.2943 | 15.8537 | |
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| 0.0 | 555.0 | 5000 | 0.3182 | 17.0732 | |
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| 0.0 | 666.0 | 6000 | 0.3501 | 18.9024 | |
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| 0.0 | 777.0 | 7000 | 0.3732 | 16.4634 | |
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| 0.0 | 888.0 | 8000 | 0.4025 | 17.0732 | |
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| 0.0 | 999.0 | 9000 | 0.4178 | 20.1220 | |
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| 0.0 | 1111.0 | 10000 | 0.4385 | 17.0732 | |
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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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