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preszzz/
drone-audio-detection-05-17-trial-0

Name: drone-audio-detection-05-17-trial-0
Availability: InStock

transformers

tensorboard

safetensors

audio-spectrogram-transformer

audio-classification

generated_from_trainer

MIT/ast-finetuned-audioset-10-10-0.4593

finetune

bsd-3-clause

endpoints_compatible

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drone-audio-detection-05-17-trial-0

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0131
Accuracy: 0.996
Precision: 0.9987
Recall: 0.9962
F1: 0.9974

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: 1.1463891217797098e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1651375762118582
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.0441	1.0	63	0.0255	0.992	0.9987	0.9910	0.9949
0.0176	2.0	126	0.0160	0.996	1.0	0.9949	0.9974
0.0027	3.0	189	0.0128	0.9955	0.9987	0.9955	0.9971
0.0003	4.0	252	0.0132	0.9955	0.9981	0.9962	0.9971
0.0002	4.928	310	0.0131	0.996	0.9987	0.9962	0.9974

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

preszzz/drone-audio-detection-05-17-trial-0

drone-audio-detection-05-17-trial-0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

preszzz/
drone-audio-detection-05-17-trial-0