---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- audio-classification
- deepfake
- audio-spoof
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-960h-asv19-deepfake
  results: []
---

<!-- 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. -->

# hubert-base-960h-asv19-deepfake

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0624
- Accuracy: 0.9918
- Far: 0.0024
- Frr: 0.0088
- Eer: 0.0056

## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Far    | Frr    | Eer    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|
| 0.0726        | 0.79  | 5000  | 0.1522          | 0.9648   | 0.0027 | 0.0389 | 0.0208 |
| 0.0338        | 1.58  | 10000 | 0.0995          | 0.9852   | 0.0024 | 0.0162 | 0.0093 |
| 0.0256        | 2.36  | 15000 | 0.0434          | 0.9940   | 0.0027 | 0.0063 | 0.0045 |
| 0.0294        | 3.15  | 20000 | 0.0756          | 0.9899   | 0.0020 | 0.0111 | 0.0065 |
| 0.0175        | 3.94  | 25000 | 0.0624          | 0.9918   | 0.0024 | 0.0088 | 0.0056 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.2