wav2vec2-large-xls-r-300m-albanian-colab
| Property | Value |
|---|---|
| Base Model | facebook/wav2vec2-xls-r-300m |
| Training Dataset | Common Voice Albanian |
| Author | Alimzhan |
| Framework | PyTorch 2.1.0 |
What is wav2vec2-large-xls-r-300m-albanian-colab?
This is a specialized speech recognition model fine-tuned specifically for the Albanian language. It builds upon Facebook's wav2vec2-xls-r-300m architecture, adapted to handle Albanian speech recognition tasks through careful fine-tuning on the Common Voice Albanian dataset.
Implementation Details
The model employs advanced training techniques including mixed precision training with Native AMP and utilizes the Adam optimizer with carefully tuned parameters (β1=0.9, β2=0.999, ε=1e-08). The training process spans 30 epochs with a linear learning rate scheduler and 500 warmup steps.
- Learning rate: 0.0003
- Batch size: 32 (16 per batch with 2 gradient accumulation steps)
- Evaluation batch size: 8
- Training epochs: 30
Core Capabilities
- Albanian speech recognition
- Support for Common Voice dataset integration
- Optimized for production deployment
- Mixed precision training support
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically optimized for Albanian language speech recognition, building upon the robust wav2vec2-xls-r-300m architecture while incorporating specialized training for Albanian language patterns.
Q: What are the recommended use cases?
The model is ideal for Albanian speech recognition tasks, including transcription services, voice commands, and audio content analysis in Albanian language contexts.
