distil-whisper-large-v3-tr

distil-whisper-large-v3-tr

Model Description

distil-whisper-large-v3-tr is a distilled version of the Whisper model, fine-tuned for Turkish language tasks. This model has been trained and evaluated using a comprehensive dataset to achieve high accuracy in Turkish speech recognition.

Training and Evaluation Metrics

The model was trained and evaluated using the wandb tool, with the following results:

Evaluation Metrics

• Cross-Entropy Loss (eval/ce_loss): 0.53218
• Epoch (eval/epoch): 28
• KL Loss (eval/kl_loss): 0.34883
• Total Loss (eval/loss): 0.77457
• Evaluation Time (eval/time): 397.1784 seconds
• Word Error Rate (eval/wer): 14.43288%
• Orthographic Word Error Rate (eval/wer_ortho): 21.55298%

Training Metrics

• Cross-Entropy Loss (train/ce_loss): 0.04695
• Epoch (train/epoch): 28
• KL Loss (train/kl_loss): 0.24143
• Learning Rate (train/learning_rate): 0.0001
• Total Loss (train/loss): 0.27899
• Training Time (train/time): 12426.92106 seconds

Run History

Overall Metrics

• Real-Time Factor (all/rtf): 392.23396
• Word Error Rate (all/wer): 14.33829

Common Voice 17.0 Turkish Pseudo-Labelled Dataset

• Real-Time Factor (common_voice_17_0_tr_pseudo_labelled/test/rtf): 392.23396
• Word Error Rate (common_voice_17_0_tr_pseudo_labelled/test/wer): 14.33829

Author

Sercan Çepni
Email: [email protected]

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For any questions or further information, please feel free to contact the author.