wav2vec2-base_music_speech_both_classification – AI Model by FerhatDk | AlphaNeural AI

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FerhatDk/
wav2vec2-base_music_speech_both_classification

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audio-classification

generated_from_trainer

endpoints_compatible

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wav2vec2-base_music_speech_both_classification

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0586
Accuracy: 0.9847

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 500
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9458	1.0	66	0.8468	0.7405
0.3785	2.0	132	0.2951	0.9771
0.1762	3.0	198	0.2639	0.9313
0.134	4.0	264	0.1084	0.9771
0.0782	5.0	330	0.0877	0.9771
0.0568	6.0	396	0.0912	0.9771
0.0122	7.0	462	0.4056	0.9198
0.059	8.0	528	0.0586	0.9847

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3