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---
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library_name: transformers
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license: apache-2.0
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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_0
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model-index:
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- name: 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:
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type:
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config: el
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split: None
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args: el
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metrics:
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value: 45.63223714682724
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---
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should probably proofread and complete it, then remove this comment. -->
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# whisper-small-el
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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_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8687
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- Model Preparation Time: 0.0059
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- Wer: 45.6322
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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: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- training_steps: 14
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- mixed_precision_training: Native AMP
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### Training results
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| 0.8509 | 0.0439 | 5 | 0.9019 | 0.0059 | 46.4382 |
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| 0.8082 | 0.0877 | 10 | 0.8687 | 0.0059 | 45.6322 |
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###
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- Tokenizers 0.21.0
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---
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base_model: openai/whisper-small
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datasets:
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- mozilla-foundation/common_voice_17_0
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language: el
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library_name: transformers
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license: apache-2.0
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model-index:
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- name: Finetuned openai/whisper-small on Greek
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results:
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- task:
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type: automatic-speech-recognition
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name: Speech-to-Text
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dataset:
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name: Common Voice (Greek)
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type: common_voice
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metrics:
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- type: wer
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value: 45.632
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---
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# Finetuned openai/whisper-small on 3620 Greek training audio samples from mozilla-foundation/common_voice_17_0.
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This model was created from the Mozilla.ai Blueprint:
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[speech-to-text-finetune](https://github.com/mozilla-ai/speech-to-text-finetune).
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## Evaluation results on 1701 audio samples of Greek:
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### Baseline model (before finetuning) on Greek
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- Word Error Rate: 46.392
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- Loss: 0.902
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### Finetuned model (after finetuning) on Greek
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- Word Error Rate: 45.632
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- Loss: 0.869
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