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---
license: mit
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: VIT-VoxCelebSpoof-ConstantQ-Synthetic-Voice-Detection
results: []
datasets:
- MattyB95/VoxCelebSpoof
language:
- en
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# VIT-VoxCelebSpoof-ConstantQ-Synthetic-Voice-Detection
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
It achieves the following results on the evaluation set:
- Accuracy: 1.0
- F1: 1.0
- Loss: 0.0000
- Precision: 1.0
- Recall: 1.0
## 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 | Accuracy | F1 | Validation Loss | Precision | Recall |
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:|
| 0.0 | 1.0 | 29527 | 0.9999 | 0.9999 | 0.0006 | 0.9999 | 1.0 |
| 0.0 | 2.0 | 59054 | 1.0000 | 1.0000 | 0.0002 | 1.0 | 0.9999 |
| 0.0 | 3.0 | 88581 | 1.0 | 1.0 | 0.0000 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |