README.md

metadata

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

AST-ASVspoof2019-Synthetic-Voice-Detection

This model is a fine-tuned version of 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