metadata
license: mit
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: VIT-VoxCelebSpoof-MFCC-Synthetic-Voice-Detection
results: []
datasets:
- MattyB95/VoxCelebSpoof
language:
- en
VIT-VoxCelebSpoof-MFCC-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:
- Loss: 0.0001
- Accuracy: 1.0000
- F1: 1.0000
- Precision: 1.0
- Recall: 1.0000
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 29527 | 0.0006 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
| 0.0 | 2.0 | 59054 | 0.0002 | 0.9999 | 1.0000 | 1.0000 | 1.0000 |
| 0.0 | 3.0 | 88581 | 0.0001 | 1.0000 | 1.0000 | 1.0 | 1.0000 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1