speech-commands_hubert-base – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
speech-commands_hubert-base

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audio-classification

generated_from_trainer

facebook/hubert-base-ls960

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superb_ks_42

This model is a fine-tuned version of facebook/hubert-base-ls960 on the superb dataset. It achieves the following results on the evaluation set:

Loss: 0.0857
Accuracy: 0.9834

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
1.5858	1.0	1597	0.1746	0.9701
0.2268	2.0	3194	0.1038	0.9773
0.1937	3.0	4791	0.0887	0.9797
0.163	4.0	6388	0.0786	0.9826
0.1468	5.0	7985	0.0982	0.9815
0.1327	6.0	9582	0.0888	0.9821
0.1175	7.0	11179	0.0967	0.9812
0.1164	8.0	12776	0.0922	0.9815
0.1023	9.0	14373	0.0875	0.9828
0.0983	10.0	15970	0.0857	0.9834

Framework versions

Transformers 4.40.1
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1