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--- |
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language: |
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- en |
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metrics: |
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- wer |
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pipeline_tag: automatic-speech-recognition |
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--- |
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# Model Card: LEVI Whisper Medium.en Fine-Tuned Model |
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## Model Information |
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- **Model Name:** levicu/LEVI_whisper_medium.en |
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- **Description:** This model is a fine-tuned version of the OpenAI Whisper Medium.en model, tailored for speech recognition tasks using the LEVI v2 dataset, which consists of classroom audiovisual recording data. |
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- **Model Architecture:** openai/whisper-medium.en |
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- **Dataset:** LEVI_LoFi_v2/TRAIN (per-utterance transcript and 16k WAV audio) |
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- both student and tutor speech were used |
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- manifest: LEVI_LoFi_v2_TRAIN_punc+cased.csv- |
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## Training Details |
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- **Training Procedure:** |
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- LoRA Parameter Efficient Fine-tuning technique with the following parameters: |
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- r=32 |
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- lora_alpha=64 |
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- target_modules=["q_proj", "v_proj"] |
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- lora_dropout=0.05 |
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- bias="none" |
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- INT8 quantization |
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- Trained for 3 epochs with a learning rate of 1e-4 and warmup steps of 100 without gradient accumulation. |
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- **Evaluation Metrics:** Word Error Rate (WER) |
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## Evaluation |
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- **Testing Data** |
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- Test Data 1: LoFi Students (LEVI_LoFi_v2_TEST_punc+cased_student) |
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- Test Data 2: LoFi Tutors (LEVI_LoFi_v2_TEST_punc+cased_tutor) |
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- Test Data 3: HiFi Students (LEVI_orig11_HiFi_punc+cased_student) |
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- Test Data 4: HiFi Tutor (LEVI_orig11_HiFi_punc+cased_tutor) |
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- **Metric** |
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- Word Error Rate (WER) |
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- **Results** |
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- Test Data 1: 38.3% |
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- Test Data 2: 13.8% |
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- Test Data 3: 42.8% |
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- Test Data 4: 16.1% |
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## Usage |
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- **Usage:** The model can be used for speech recognition tasks. Inputs should be audio files and the model outputs transcriptions. |
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## Limitations and Ethical Considerations |
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- **Limitations:** None provided. |
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- **Ethical Considerations:** Consider the ethical implications of using this model, particularly in scenarios involving sensitive or private information. |
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## License |
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- **License:** Not specified. |
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## Contact Information |
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- **Contact:** For questions, feedback, or support regarding the model, please contact [email protected] or [email protected]. |