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Model: Sercan/distil-whisper-large-v3-tr
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wandb
checkpoint-*/
distil-large-v3-init

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---
language:
- "tr"
thumbnail: "url_to_thumbnail"
tags:
- speech-recognition
- Turkish
- ASR
license: "apache-2.0"
datasets:
- common_voice
metrics:
- wer
- cer
base_model: "openai/whisper-large-v3"
---
# 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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