metadata
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: 0.9696969696969697
deeepfake-audio-Recognition-ttoo
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1858
- Accuracy: 0.9697
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 |
|---|---|---|---|---|
| 0.6477 | 1.0 | 33 | 0.5411 | 0.8182 |
| 0.5099 | 2.0 | 66 | 0.4458 | 0.7879 |
| 0.3855 | 3.0 | 99 | 0.5405 | 0.7727 |
| 0.2943 | 4.0 | 132 | 0.2268 | 0.9394 |
| 0.2818 | 5.0 | 165 | 0.2283 | 0.9091 |
| 0.2378 | 6.0 | 198 | 0.1955 | 0.9394 |
| 0.1321 | 7.0 | 231 | 0.2335 | 0.9394 |
| 0.1688 | 8.0 | 264 | 0.2009 | 0.9545 |
| 0.07 | 9.0 | 297 | 0.2629 | 0.9242 |
| 0.0413 | 10.0 | 330 | 0.2156 | 0.9545 |
| 0.0229 | 11.0 | 363 | 0.3189 | 0.9394 |
| 0.0062 | 12.0 | 396 | 0.3850 | 0.9242 |
| 0.0159 | 13.0 | 429 | 0.2462 | 0.9394 |
| 0.0179 | 14.0 | 462 | 0.1904 | 0.9697 |
| 0.0059 | 15.0 | 495 | 0.1844 | 0.9697 |
| 0.0248 | 16.0 | 528 | 0.1858 | 0.9697 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2