Audioclasshem – AI Model by Hemg | AlphaNeural AI

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Hemg/
Audioclasshem

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audio-classification

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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Audioclasshem

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

Loss: 2.6526
Accuracy: 0.0531

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: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8	3	2.6340	0.0796
No log	1.87	7	2.6406	0.0619
2.6341	2.93	11	2.6515	0.0265
2.6341	4.0	15	2.6554	0.0265
2.6341	4.8	18	2.6591	0.0265
2.6233	5.87	22	2.6534	0.0354
2.6233	6.93	26	2.6536	0.0531
2.6144	8.0	30	2.6527	0.0619
2.6144	8.8	33	2.6536	0.0354
2.6144	9.87	37	2.6529	0.0354
2.614	10.93	41	2.6521	0.0442
2.614	12.0	45	2.6526	0.0531
2.614	12.8	48	2.6526	0.0531

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0