mozilla-foundation/common_voice_17_0
Updated • 3.58k • 49
How to use xbilek25/wme_30s_speed_20_1.0 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="xbilek25/wme_30s_speed_20_1.0") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("xbilek25/wme_30s_speed_20_1.0")
model = AutoModelForSpeechSeq2Seq.from_pretrained("xbilek25/wme_30s_speed_20_1.0", device_map="auto")This model is a fine-tuned version of openai/whisper-medium.en 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 |
|---|---|---|---|---|
| No log | 0 | 0 | 1.8678 | 47.3362 |
| 0.7443 | 0.3333 | 88 | 1.1949 | 34.2315 |
| 0.52 | 1.0038 | 176 | 1.1157 | 31.9045 |
| 0.2008 | 1.3371 | 264 | 1.0985 | 31.6901 |
Base model
openai/whisper-medium.en