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--- |
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language: |
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- ja |
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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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- mozilla-foundation/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: Whisper Base Japanese |
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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: mozilla-foundation/common_voice_11_0 ja |
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type: mozilla-foundation/common_voice_11_0 |
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config: ja |
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split: test |
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args: ja |
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metrics: |
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- name: Wer |
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type: wer |
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value: 21.991788980318223 |
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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 |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_11_0 ja dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6532 |
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- Wer: 21.9918 |
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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: 16 |
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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: 500 |
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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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| 0.3273 | 3.02 | 1000 | 0.4225 | 20.8253 | |
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| 0.0923 | 7.0 | 2000 | 0.4643 | 21.2200 | |
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| 0.0164 | 10.02 | 3000 | 0.5403 | 22.9627 | |
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| 0.006 | 14.01 | 4000 | 0.5820 | 21.0861 | |
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| 0.0046 | 17.02 | 5000 | 0.5852 | 22.0728 | |
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| 0.0034 | 21.01 | 6000 | 0.6113 | 21.6623 | |
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| 0.0028 | 24.03 | 7000 | 0.6582 | 22.3266 | |
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| 0.0025 | 28.01 | 8000 | 0.6350 | 22.2332 | |
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| 0.0029 | 32.0 | 9000 | 0.6468 | 22.1098 | |
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| 0.0014 | 35.02 | 10000 | 0.6532 | 21.9918 | |
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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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