speech_commands-wav2vec2-base – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
speech_commands-wav2vec2-base

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audio-classification

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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superb_ks_42

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

Loss: 0.0853
Accuracy: 0.9846

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: 32
eval_batch_size: 4
seed: 42
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
1.25	1.0	1597	0.1755	0.9582
0.2502	2.0	3194	0.1402	0.9713
0.2218	3.0	4791	0.0956	0.9803
0.1746	4.0	6388	0.0917	0.9797
0.17	5.0	7985	0.0893	0.9807
0.1431	6.0	9582	0.0933	0.9810
0.1238	7.0	11179	0.0958	0.9831
0.116	8.0	12776	0.0970	0.9834
0.0995	9.0	14373	0.0853	0.9846
0.0985	10.0	15970	0.0829	0.9838

Framework versions

Transformers 4.40.1
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1