wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan – AI Model by leo-kwan | AlphaNeural AI

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leo-kwan/
wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan

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audio-classification

generated_from_trainer

m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres

endpoints_compatible

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wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan

This model is a fine-tuned version of m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres on the GTZAN dataset. It achieves the following results on the evaluation set:

Loss: 0.6843
Accuracy: 0.98

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.1932	0.9976	53	2.1037	0.82
1.9212	1.9953	106	1.8040	0.8267
1.6379	2.9929	159	1.5650	0.8667
1.4604	3.9906	212	1.3201	0.9267
1.2249	4.9882	265	1.1253	0.94
1.075	5.9859	318	0.9814	0.96
0.911	6.9835	371	0.8447	0.9667
0.852	8.0	425	0.7628	0.9667
0.7625	8.9976	478	0.7117	0.9733
0.7099	9.9765	530	0.6843	0.98

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1