legacy-datasets/common_voice
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How to use Jana1994/wav2vec2-large-xls-r-300m-jana-colab with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Jana1994/wav2vec2-large-xls-r-300m-jana-colab") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("Jana1994/wav2vec2-large-xls-r-300m-jana-colab")
model = AutoModelForCTC.from_pretrained("Jana1994/wav2vec2-large-xls-r-300m-jana-colab")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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.6444 | 1.67 | 200 | 2.9379 | 1.0 |
| 2.7964 | 3.33 | 400 | 1.9912 | 0.9927 |
| 1.1945 | 5.0 | 600 | 0.9492 | 0.7889 |
| 0.6065 | 6.67 | 800 | 0.8534 | 0.7137 |
| 0.3859 | 8.33 | 1000 | 0.8933 | 0.6689 |
| 0.2724 | 10.0 | 1200 | 0.8913 | 0.6497 |
Base model
facebook/wav2vec2-xls-r-300m