mozilla-foundation/common_voice_17_0
Updated • 6.15k • 18
How to use augustinjianu/whisper-base-ro with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="augustinjianu/whisper-base-ro") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("augustinjianu/whisper-base-ro")
model = AutoModelForSpeechSeq2Seq.from_pretrained("augustinjianu/whisper-base-ro")This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 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 |
|---|---|---|---|---|
| 0.366 | 1.7730 | 1000 | 0.4236 | 35.2256 |
| 0.1676 | 3.5461 | 2000 | 0.3700 | 31.5503 |
| 0.0752 | 5.3191 | 3000 | 0.3683 | 30.3287 |
| 0.0355 | 7.0922 | 4000 | 0.3841 | 30.1756 |
| 0.025 | 8.8652 | 5000 | 0.4003 | 30.0011 |
| 0.0106 | 10.6383 | 6000 | 0.4232 | 31.6820 |
| 0.0067 | 12.4113 | 7000 | 0.4380 | 31.4221 |
| 0.0043 | 14.1844 | 8000 | 0.4520 | 30.1613 |
| 0.0038 | 15.9574 | 9000 | 0.4594 | 30.1079 |
| 0.0032 | 17.7305 | 10000 | 0.4626 | 31.0909 |
Base model
openai/whisper-base