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--- |
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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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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Chinese Base |
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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: google/fleurs cmn_hans_cn |
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type: google/fleurs |
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config: cmn_hans_cn |
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split: test |
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args: cmn_hans_cn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 14.92818317087243 |
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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 Chinese Base |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs cmn_hans_cn dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2910 |
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- Wer: 14.9282 |
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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: 64 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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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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| 0.0013 | 19.01 | 1000 | 0.2910 | 14.9282 | |
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| 0.0005 | 39.0 | 2000 | 0.3185 | 15.6327 | |
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| 0.0002 | 58.01 | 3000 | 0.3369 | 15.6965 | |
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| 0.0002 | 78.0 | 4000 | 0.3480 | 16.0669 | |
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| 0.0001 | 98.0 | 5000 | 0.3537 | 16.0548 | |
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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 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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