wav2vec2-xlsr-1b-ru
| Property | Value |
|---|---|
| Base Model | facebook/wav2vec2-xls-r-1b |
| Task | Speech Recognition (Russian) |
| Best WER | 9.71% |
| Training Dataset | Common Voice |
| Model Hub | HuggingFace |
What is wav2vec2-xlsr-1b-ru?
wav2vec2-xlsr-1b-ru is a specialized speech recognition model fine-tuned specifically for the Russian language. Built upon Facebook's wav2vec2-xls-r-1b architecture, this model has been optimized through extensive training to achieve impressive speech recognition accuracy with a Word Error Rate (WER) of just 9.71%.
Implementation Details
The model underwent a comprehensive training process using carefully selected hyperparameters. Training was conducted over 10 epochs using the Adam optimizer with a learning rate of 5e-05, incorporating linear learning rate scheduling with 500 warmup steps. The implementation utilized mixed-precision training with Native AMP for optimal performance.
- Batch sizes: 32 for training, 8 for evaluation
- Training methodology: Progressive improvement from initial WER of 35.75% to final 9.71%
- Optimization: Adam optimizer with betas=(0.9,0.999) and epsilon=1e-08
Core Capabilities
- High-accuracy Russian speech recognition
- Robust performance with 9.71% WER on evaluation set
- Efficient processing with mixed-precision capabilities
- Gradual performance improvement demonstrated through training
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized optimization for Russian language speech recognition, achieving a notably low WER of 9.71%. It benefits from the robust wav2vec2-xls-r-1b architecture while being specifically tailored for Russian language processing.
Q: What are the recommended use cases?
The model is ideal for Russian speech recognition tasks, including transcription services, voice command systems, and automated subtitling. Its low WER makes it suitable for production environments where accuracy is crucial.
