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---
license: mit
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
datasets:
- audiofolder
- LanceaKing/asvspoof2019
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: AST-ASVspoof2019-Synthetic-Voice-Detection
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6294477539848655
- name: F1
type: f1
value: 0.7685655387400071
- name: Precision
type: precision
value: 0.8743850817984212
- name: Recall
type: recall
value: 0.6855938284894152
language:
- en
---
<!-- 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. -->
# AST-ASVspoof2019-Synthetic-Voice-Detection
This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss:
- Accuracy:
- F1:
- Precision:
- Recall:
## 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: 5e-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
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------------------------------:|:-----:|:----:|:-------------------------------------:|:--------:|:------:|:---------:|:------:|
| | 1.0 | | | | | | |
| | 2.0 | | | | | | |
| | 3.0 | | | | | | |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0 |