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README.md
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This model was carefully trained on a dataset of **Kalaallisut** audio files paired with transcriptions. Special care was taken to avoid overfitting, which occurred in earlier versions of this fine-tuning process. After reworking the training approach, including tweaking hyperparameters and employing early stopping to monitor model performance, the final **Word Error Rate (WER)** was reduced significantly to:
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- **Final Validation WER:
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### ⚙️ Features and Improvements
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### 📊 Performance Metrics
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- **Word Error Rate (WER)**:
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- **Train Loss**:
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### How to Use
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This model was carefully trained on a dataset of **Kalaallisut** audio files paired with transcriptions. Special care was taken to avoid overfitting, which occurred in earlier versions of this fine-tuning process. After reworking the training approach, including tweaking hyperparameters and employing early stopping to monitor model performance, the final **Word Error Rate (WER)** was reduced significantly to:
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- **Final Validation WER: 0.95%%**
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### ⚙️ Features and Improvements
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### 📊 Performance Metrics
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- **Word Error Rate (WER)**: 0.95%%
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- **Train Loss**: 1.93 after 5 epochs
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### How to Use
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