legacy-datasets/common_voice
Updated • 1.48k • 148
How to use burakyldrm/wav2vec2-burak with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="burakyldrm/wav2vec2-burak") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("burakyldrm/wav2vec2-burak")
model = AutoModelForCTC.from_pretrained("burakyldrm/wav2vec2-burak", device_map="auto")This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.8973 | 7.02 | 400 | 0.7101 | 0.7295 |
| 0.3118 | 14.03 | 800 | 0.5377 | 0.5062 |
| 0.1272 | 21.05 | 1200 | 0.5462 | 0.4296 |
| 0.0723 | 28.07 | 1600 | 0.4954 | 0.3969 |