audio-voilence-detection-vii – AI Model by Hemg | AlphaNeural AI

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Hemg/
audio-voilence-detection-vii

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audio-classification

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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audio-voilence-detection-vii

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: 0.6731
Accuracy: 0.6

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: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6671	0.95	9	0.4106	0.8933
0.674	2.0	19	0.6732	0.6
0.7163	2.95	28	0.6747	0.6
0.6465	4.0	38	0.6730	0.6
0.7088	4.95	47	0.6730	0.6
0.6445	6.0	57	0.6730	0.6
0.7132	6.95	66	0.6731	0.6
0.6201	7.58	72	0.6731	0.6

Framework versions

Transformers 4.39.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2