genre-recognizer-finetuned-gtzan_dset – AI Model by pedromatias97 | AlphaNeural AI

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pedromatias97/
genre-recognizer-finetuned-gtzan_dset

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audio-classification

generated_from_trainer

ntu-spml/distilhubert

endpoints_compatible

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music-genre-detector-finetuned-gtzan_dset

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: 0.3892
Accuracy: 0.8972
Precision: 0.8989
Recall: 0.8972
F1: 0.8974

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: 9e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
2.2319	0.98	49	1.5808	0.5263	0.5682	0.5263	0.4767
1.2682	1.98	99	0.9750	0.7556	0.7524	0.7556	0.7510
0.9462	2.99	149	0.7403	0.7945	0.7964	0.7945	0.7921
0.5946	3.99	199	0.5921	0.8233	0.8281	0.8233	0.8214
0.4095	4.99	249	0.4772	0.8634	0.8663	0.8634	0.8638
0.3349	5.99	299	0.4167	0.8835	0.8866	0.8835	0.8841
0.2427	6.88	343	0.3892	0.8972	0.8989	0.8972	0.8974

Framework versions

Transformers 4.33.1
Pytorch 1.10.2+cu111
Datasets 2.14.5
Tokenizers 0.13.3