speechbrain/common_language
Updated • 459 • 43
How to use sanchit-gandhi/whisper-base-ft-common-language-id with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="sanchit-gandhi/whisper-base-ft-common-language-id") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("sanchit-gandhi/whisper-base-ft-common-language-id")
model = AutoModelForAudioClassification.from_pretrained("sanchit-gandhi/whisper-base-ft-common-language-id")This model is a fine-tuned version of openai/whisper-base on the common_language 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 | Accuracy |
|---|---|---|---|---|
| 2.5291 | 1.0 | 694 | 2.4787 | 0.4806 |
| 1.5801 | 2.0 | 1388 | 1.6258 | 0.6260 |
| 1.0144 | 3.0 | 2082 | 1.2886 | 0.6816 |
| 0.7442 | 4.0 | 2776 | 1.0783 | 0.7237 |
| 0.4802 | 5.0 | 3470 | 1.0582 | 0.7266 |
| 0.3378 | 6.0 | 4164 | 1.0173 | 0.7417 |
| 0.1941 | 7.0 | 4858 | 1.0054 | 0.7446 |
| 0.1424 | 8.0 | 5552 | 1.0213 | 0.7508 |
| 0.1242 | 9.0 | 6246 | 1.0567 | 0.7495 |
| 0.1527 | 10.0 | 6940 | 1.0725 | 0.7525 |