---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: deeepfake-audio-Recognition-ttoo
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9545454545454546
---

<!-- 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. -->

# deeepfake-audio-Recognition-ttoo

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2288
- Accuracy: 0.9545

## 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: 3e-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
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6417        | 1.0   | 33   | 0.5774          | 0.7879   |
| 0.4818        | 2.0   | 66   | 0.3792          | 0.8485   |
| 0.2756        | 3.0   | 99   | 0.3066          | 0.8788   |
| 0.3106        | 4.0   | 132  | 0.1951          | 0.9545   |
| 0.2138        | 5.0   | 165  | 0.2078          | 0.9394   |
| 0.0988        | 6.0   | 198  | 0.3227          | 0.9091   |
| 0.1043        | 7.0   | 231  | 0.2893          | 0.9394   |
| 0.0808        | 8.0   | 264  | 0.2177          | 0.9545   |
| 0.1312        | 9.0   | 297  | 0.2846          | 0.9091   |
| 0.0667        | 10.0  | 330  | 0.1955          | 0.9545   |
| 0.0513        | 11.0  | 363  | 0.2553          | 0.9545   |
| 0.0217        | 12.0  | 396  | 0.1708          | 0.9545   |
| 0.0136        | 13.0  | 429  | 0.1641          | 0.9545   |
| 0.0236        | 14.0  | 462  | 0.2203          | 0.9545   |
| 0.0097        | 15.0  | 495  | 0.2253          | 0.9545   |
| 0.003         | 16.0  | 528  | 0.2288          | 0.9545   |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2