legacy-datasets/common_voice
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How to use ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8")
model = AutoModelForCTC.from_pretrained("ai-project/wav2vec2-xlsr-large-vi-aiclass-20221-group-8")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 |
|---|---|---|---|---|
| 5.3934 | 3.45 | 400 | 3.4806 | 1.0 |
| 2.3392 | 6.9 | 800 | 2.1210 | 0.9011 |
| 1.1786 | 10.34 | 1200 | 2.4091 | 0.7807 |
| 0.779 | 13.79 | 1600 | 2.7128 | 0.7621 |
| 0.5645 | 17.24 | 2000 | 3.0103 | 0.7428 |
| 0.4329 | 20.69 | 2400 | 3.0804 | 0.7219 |
| 0.3455 | 24.14 | 2800 | 3.1075 | 0.7190 |
| 0.2803 | 27.59 | 3200 | 3.2659 | 0.7160 |