You can deploy this model and start earning money today!

polinaZaroko/
ast-gtzan

Name: ast-gtzan
Availability: InStock

tensorboard

safetensors

audio-spectrogram-transformer

generated_from_trainer

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

finetune

bsd-3-clause

Views

No views yet

ast-gtzan

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: 0.6011
Accuracy: 0.87

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	100	1.2436	0.575
No log	2.0	200	0.6776	0.765
No log	3.0	300	0.5227	0.815
No log	4.0	400	0.6133	0.805
0.6647	5.0	500	0.6569	0.82
0.6647	6.0	600	0.6299	0.855
0.6647	7.0	700	0.6213	0.85
0.6647	8.0	800	0.6398	0.85
0.6647	9.0	900	0.6011	0.87
0.0343	10.0	1000	0.6092	0.87

Framework versions

Transformers 4.39.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.15.2

polinaZaroko/ast-gtzan

ast-gtzan

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

polinaZaroko/
ast-gtzan