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: turkelf@gmail.com
For any questions or further information, please feel free to contact the author.
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openai/whisper-large-v3
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