speech to text
Collection
Speech to text models • 8 items • Updated
How to use simpragma/breeze-listen-dsw-small-ml with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="simpragma/breeze-listen-dsw-small-ml") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("simpragma/breeze-listen-dsw-small-ml")
model = AutoModelForSpeechSeq2Seq.from_pretrained("simpragma/breeze-listen-dsw-small-ml")This model is a fine-tuned version of openai/whisper-small on the common_voice_16_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 |
|---|---|---|---|---|
| 0.4577 | 1.02 | 100 | 0.4824 | 58.3874 |
| 0.1781 | 2.04 | 200 | 0.3066 | 41.0658 |
| 0.0935 | 3.06 | 300 | 0.2903 | 35.6441 |
| 0.057 | 5.0 | 400 | 0.3289 | 36.6172 |
| 0.0285 | 6.03 | 500 | 0.3425 | 35.3197 |
| 0.0203 | 7.05 | 600 | 0.3647 | 34.3837 |
Base model
openai/whisper-small