asr-malayalam/spring_ml_conversation
Viewer • Updated • 24.1k • 265
How to use chan73/whisper-small-ml with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="chan73/whisper-small-ml") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("chan73/whisper-small-ml")
model = AutoModelForSpeechSeq2Seq.from_pretrained("chan73/whisper-small-ml")This model is a fine-tuned version of openai/whisper-small on the Spring ML dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.2293 | 3.8502 | 500 | 0.3561 | 91.3568 | 60.6804 |
Base model
openai/whisper-small