Hubert-base-superb – AI Model by Elliotte | AlphaNeural AI

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Hubert-base-superb

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Hubert-base-superb

This model is a fine-tuned version of ntu-spml/distilhubert on the superb dataset. It achieves the following results on the evaluation set:

Loss: 0.6712
Wer: 0.4781

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: 0.001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.7884	0.8	500	0.8900	0.6940
0.6603	1.6	1000	0.7378	0.6103
0.5401	2.4	1500	0.7107	0.5762
0.4604	3.2	2000	0.6563	0.5320
0.3936	4.0	2500	0.6315	0.5244
0.3186	4.8	3000	0.6525	0.5007
0.2727	5.6	3500	0.6553	0.4855
0.2296	6.4	4000	0.6712	0.4781

Framework versions

Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1