metadata
license: apache-2.0
base_model: motheecreator/Deepfake-audio-detection
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: Deepfake-audio-detection-V2
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: 0.9972843305874898
Deepfake-audio-detection-V2
This model is a fine-tuned version of motheecreator/Deepfake-audio-detection on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0141
- Accuracy: 0.9973
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0503 | 1.0 | 1381 | 0.0514 | 0.9858 |
| 0.0327 | 2.0 | 2762 | 0.0174 | 0.9956 |
| 0.0064 | 3.0 | 4143 | 0.0221 | 0.9950 |
| 0.0003 | 4.0 | 5524 | 0.0174 | 0.9965 |
| 0.0115 | 5.0 | 6905 | 0.0141 | 0.9973 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1