distilhubert-finetuned-gtzan-v2 – AI Model by juancopi81 | AlphaNeural AI

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juancopi81/
distilhubert-finetuned-gtzan-v2

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audio-classification

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endpoints_compatible

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distilhubert-finetuned-gtzan-v2

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: 0.6385
Accuracy: 0.85

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: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8498	1.0	113	1.8925	0.46
1.2822	2.0	226	1.3237	0.65
1.0384	3.0	339	0.9066	0.73
0.5947	4.0	452	0.6975	0.81
0.4105	5.0	565	0.5710	0.87
0.3001	6.0	678	0.5835	0.84
0.1888	7.0	791	0.5841	0.82
0.2508	8.0	904	0.5339	0.84
0.0914	9.0	1017	0.5488	0.86
0.1202	10.0	1130	0.8281	0.83
0.02	11.0	1243	0.6547	0.84
0.0149	12.0	1356	0.6789	0.84
0.0135	13.0	1469	0.6385	0.85

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3