mozilla-foundation/common_voice_13_0
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How to use Stopwolf/wav2vec2-large-mms-1b-por with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Stopwolf/wav2vec2-large-mms-1b-por") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("Stopwolf/wav2vec2-large-mms-1b-por")
model = AutoModelForCTC.from_pretrained("Stopwolf/wav2vec2-large-mms-1b-por")This model is a fine-tuned version of facebook/mms-1b-all on the mozilla-foundation/common_voice_13_0 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 |
|---|---|---|---|---|
| 0.3219 | 0.55 | 500 | 0.1743 | 0.1302 |
| 0.2443 | 1.1 | 1000 | 0.1480 | 0.1206 |
| 0.2358 | 1.65 | 1500 | 0.1402 | 0.1167 |
| 0.223 | 2.21 | 2000 | 0.1364 | 0.1159 |
| 0.2213 | 2.76 | 2500 | 0.1340 | 0.1141 |
Base model
facebook/mms-1b-all