You can deploy this model and start earning money today!

rngzhi/
cs3264-project

Views

No views yet

Whipser Small - Singlish

This model is a fine-tuned version of openai/whisper-small on the National Speech Corpus(partial) dataset. It achieves the following results on the evaluation set:

Loss: 0.2020
Wer: 5.3795

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: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0068	5.01	500	0.1508	5.4137
0.001	11.01	1000	0.1691	5.0832
0.0003	16.02	1500	0.1769	5.1060
0.0006	22.01	2000	0.1840	5.0946
0.0005	28.0	2500	0.1891	5.1174
0.0003	33.02	3000	0.1933	5.2086
0.0005	39.01	3500	0.1962	5.2997
0.0002	45.0	4000	0.1991	5.3339
0.0002	50.02	4500	0.2010	5.3681
0.0003	56.01	5000	0.2020	5.3795

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.1.dev0
Tokenizers 0.15.2

rngzhi/cs3264-project

Whipser Small - Singlish

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

rngzhi/
cs3264-project