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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- 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: openai/whisper-small
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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_11_0
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type: common_voice_11_0
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config: tr
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split: test
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args: tr
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metrics:
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- name: Wer
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type: wer
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value: 16.318103103769815
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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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# openai/whisper-small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2860
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- Wer: 16.3181
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- Cer: 4.1450
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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: 8
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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: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 20000
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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 | Cer |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
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| 0.1563 | 1.0 | 2500 | 0.2524 | 19.8570 | 5.1738 |
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| 0.032 | 2.01 | 5000 | 0.2567 | 18.5627 | 4.7793 |
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| 0.013 | 3.01 | 7500 | 0.2637 | 17.7723 | 4.6664 |
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| 0.0057 | 4.02 | 10000 | 0.2703 | 17.0596 | 4.3662 |
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| 0.0012 | 5.02 | 12500 | 0.2696 | 17.8322 | 5.2286 |
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| 0.003 | 6.03 | 15000 | 0.2800 | 16.7200 | 4.2972 |
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| 0.0003 | 7.03 | 17500 | 0.2834 | 16.4091 | 4.2018 |
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| 0.0002 | 8.04 | 20000 | 0.2860 | 16.3181 | 4.1450 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.9.1.dev0
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- Tokenizers 0.13.2
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