mozilla-foundation/common_voice_17_0
Updated • 5.54k • 16
How to use ray0303/whisper-small-tk with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ray0303/whisper-small-tk") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ray0303/whisper-small-tk")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ray0303/whisper-small-tk")This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 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 |
|---|---|---|---|---|
| 0.0083 | 14.0845 | 1000 | 1.1117 | 60.3571 |
| 0.0003 | 28.1690 | 2000 | 1.2099 | 57.7041 |
| 0.0002 | 42.2535 | 3000 | 1.2640 | 58.0102 |
| 0.0001 | 56.3380 | 4000 | 1.2973 | 58.1378 |
| 0.0001 | 70.4225 | 5000 | 1.3114 | 57.9337 |
Base model
openai/whisper-small