mozilla-foundation/common_voice_13_0
Updated • 1.62k • 5
How to use ClementXie/whisper-small with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ClementXie/whisper-small") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ClementXie/whisper-small")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ClementXie/whisper-small")This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 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 |
|---|---|---|---|---|---|
| 0.2057 | 0.41 | 500 | 0.2216 | 72.6095 | 16.9089 |
Base model
openai/whisper-small