MattyB95/VoxCelebSpoof
Updated • 295
How to use MattyB95/VIT-VoxCelebSpoof-Mel_Spectrogram-Synthetic-Voice-Detection with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="MattyB95/VIT-VoxCelebSpoof-Mel_Spectrogram-Synthetic-Voice-Detection")
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png") # Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("MattyB95/VIT-VoxCelebSpoof-Mel_Spectrogram-Synthetic-Voice-Detection")
model = AutoModelForImageClassification.from_pretrained("MattyB95/VIT-VoxCelebSpoof-Mel_Spectrogram-Synthetic-Voice-Detection")This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None 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 | Accuracy | F1 | Validation Loss | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0048 | 1.0 | 29527 | 0.9998 | 0.9999 | 0.0010 | 0.9998 | 1.0 |
| 0.0 | 2.0 | 59054 | 0.0006 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
| 0.0 | 3.0 | 88581 | 0.0002 | 1.0000 | 1.0000 | 1.0000 | 1.0 |
Base model
google/vit-base-patch16-224-in21k