transformers tensorboard safetensors vit image-classification generated_from_trainer en dataset:MattyB95/VoxCelebSpoof base_model:google/vit-base-patch16-224-in21k license:mit autotrain_compatible endpoints_compatible region:us
---
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
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# 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