distilhubert-finetuned-VD – AI Model by NiloofarMomeni | AlphaNeural AI

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NiloofarMomeni/
distilhubert-finetuned-VD

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audio-classification

generated_from_trainer

ntu-spml/distilhubert

endpoints_compatible

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distilhubert-finetuned-VD

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: 0.7226
Accuracy: 0.8933

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: 10
eval_batch_size: 10
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: 25
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3302	1.0	195	0.3716	0.8800
0.6059	2.0	390	0.5195	0.8090
0.4938	3.0	585	1.0102	0.6260
0.836	4.0	780	1.1662	0.6742
0.2234	5.0	975	0.6792	0.8389
0.1444	6.0	1170	0.9137	0.8239
0.2986	7.0	1365	0.7987	0.8623
0.0004	8.0	1560	1.5075	0.7687
0.0005	9.0	1755	0.7226	0.8933
0.0002	10.0	1950	0.8246	0.8829
0.0002	11.0	2145	1.4227	0.8129
0.0001	12.0	2340	1.0478	0.8665
0.0001	13.0	2535	1.3328	0.8322
0.0001	14.0	2730	1.3480	0.8347
0.0001	15.0	2925	1.3559	0.8370
0.0	16.0	3120	1.3589	0.8407
0.0	17.0	3315	1.3706	0.8410
0.0	18.0	3510	1.3831	0.8410
0.0	19.0	3705	1.3954	0.8410
0.0	20.0	3900	1.4027	0.8412
0.0	21.0	4095	1.4132	0.8409
0.0	22.0	4290	1.4218	0.8407
0.0	23.0	4485	1.4272	0.8407
0.0	24.0	4680	1.4321	0.8399
0.0	25.0	4875	1.4337	0.8399

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2