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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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- metrics:
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- - wer
 
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  model-index:
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- - name: whisper-small-el
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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_17_0
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- type: common_voice_17_0
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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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- - name: Wer
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- type: wer
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- value: 45.63223714682724
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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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-
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- # whisper-small-el
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-
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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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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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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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-
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- ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer |
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- |:-------------:|:------:|:----:|:---------------:|:----------------------:|:-------:|
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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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- ### Framework versions
 
 
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- - Transformers 4.48.3
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- - Pytorch 2.5.1+cu124
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- - Datasets 3.3.1
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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