deeepfake-audio-c / README.md
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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-c
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: 0.9247311827956989
---
<!-- 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-c
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: 0.3276
- Accuracy: 0.9247
## 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6297 | 1.0 | 46 | 0.5694 | 0.7849 |
| 0.461 | 2.0 | 92 | 0.4060 | 0.8602 |
| 0.3332 | 3.0 | 138 | 0.5541 | 0.7849 |
| 0.2591 | 4.0 | 184 | 0.3564 | 0.8817 |
| 0.179 | 5.0 | 230 | 0.1679 | 0.9570 |
| 0.1563 | 6.0 | 276 | 0.2795 | 0.9355 |
| 0.1129 | 7.0 | 322 | 0.3251 | 0.9247 |
| 0.0786 | 8.0 | 368 | 0.3276 | 0.9247 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2