distilhubert-finetuned-gtzan – AI Model by bbillapati | AlphaNeural AI

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bbillapati/
distilhubert-finetuned-gtzan

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audio-classification

generated_from_trainer

ntu-spml/distilhubert

endpoints_compatible

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distilhubert-finetuned-gtzan

This model is a fine-tuned version of ntu-spml/distilhubert on the gtzan dataset. It achieves the following results on the evaluation set:

Loss: 0.9983
Accuracy: 0.83

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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0454	1.0	113	1.9653	0.56
1.3054	2.0	226	1.3132	0.7
0.9479	3.0	339	0.9596	0.75
0.7291	4.0	452	0.8110	0.75
0.6033	5.0	565	0.7330	0.81
0.2973	6.0	678	0.7070	0.79
0.3574	7.0	791	0.6908	0.83
0.2078	8.0	904	0.7105	0.83
0.1569	9.0	1017	0.7204	0.83
0.0812	10.0	1130	0.7471	0.84
0.0451	11.0	1243	0.8439	0.85
0.0148	12.0	1356	0.9538	0.83
0.0096	13.0	1469	0.9364	0.84
0.0084	14.0	1582	0.9808	0.83
0.0084	15.0	1695	0.9983	0.83

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.0.1
Datasets 2.14.5
Tokenizers 0.15.0