legacy-datasets/common_voice
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How to use DylanonWic/wav2vec2-large-asr-th-2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="DylanonWic/wav2vec2-large-asr-th-2") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("DylanonWic/wav2vec2-large-asr-th-2")
model = AutoModelForCTC.from_pretrained("DylanonWic/wav2vec2-large-asr-th-2")This model was find-tune from on the CommonVoice 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 | Cer |
|---|---|---|---|---|---|
| 0.065 | 0.18 | 1000 | 0.5433 | 0.3259 | 0.0891 |
| 0.0792 | 0.36 | 2000 | 0.5453 | 0.3269 | 0.0901 |
| 0.1663 | 0.53 | 3000 | 0.4702 | 0.3299 | 0.0908 |
| 0.7971 | 0.71 | 4000 | 0.2513 | 0.3244 | 0.0889 |
| 0.7588 | 0.89 | 5000 | 0.2310 | 0.3196 | 0.0878 |