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---
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
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