This model is a fine-tuned version of MIT/ast-finetuned-audioset-12-12-0.447 on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.2875
Accuracy: 0.9171

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3681	1.0	852	0.3806	0.8626
0.1680	2.0	1704	0.3361	0.8941
0.0562	3.0	2556	0.2875	0.9171

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

trinlol/squad-sounds-ast

squad-sounds-ast

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

trinlol/
squad-sounds-ast