wav2vec2-base-finetuned-stop-classification-5 – AI Model by suyuanliu | AlphaNeural AI

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suyuanliu/
wav2vec2-base-finetuned-stop-classification-5

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audio-classification

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endpoints_compatible

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wav2vec2-base-finetuned-stop-classification-5

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: 0.1860
Accuracy: 0.9326

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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
0.6912	0.99	18	0.6572	0.6887
0.6092	1.97	36	0.5213	0.7636
0.4822	2.96	54	0.3353	0.8883
0.3866	4.0	73	0.2711	0.8978
0.3293	4.99	91	0.2208	0.9230
0.3004	5.97	109	0.2206	0.9237
0.2799	6.96	127	0.2097	0.9223
0.2688	8.0	146	0.1853	0.9305
0.2333	8.99	164	0.1850	0.9305
0.2461	9.86	180	0.1860	0.9326

Framework versions

Transformers 4.27.4
Pytorch 1.13.0
Datasets 2.7.1
Tokenizers 0.13.2