wav2musicgenre – AI Model by ramonpzg | AlphaNeural AI

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ramonpzg/
wav2musicgenre

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audio-classification

generated_from_trainer

endpoints_compatible

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wav2musicgenre

This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 1.4377
Accuracy: 0.5175

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8985	0.99	70	1.9125	0.3493
1.7093	1.99	141	1.6999	0.4356
1.6057	3.0	212	1.6076	0.4683
1.5392	4.0	283	1.5730	0.4958
1.5228	4.99	353	1.4994	0.5029
1.4261	5.99	424	1.4647	0.5131
1.3901	7.0	495	1.4556	0.5126
1.3677	8.0	566	1.4461	0.5175
1.3309	8.99	636	1.4430	0.5153
1.3152	9.89	700	1.4377	0.5175

Framework versions

Transformers 4.27.4
Pytorch 2.0.1+cu117
Datasets 2.10.1
Tokenizers 0.13.2