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anjulRajendraSharma/
wavlm-base-libri-clean-100

Name: wavlm-base-libri-clean-100
Availability: InStock

automatic-speech-recognition

librispeech_asr

generated_from_trainer

endpoints_compatible

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wavlm-libri-clean-100h-base

This model is a fine-tuned version of microsoft/wavlm-base on the LIBRISPEECH_ASR - CLEAN dataset. It achieves the following results on the evaluation set:

Loss: 0.0955
Wer: 0.0773

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: 0.0003
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.8664	0.17	300	2.8439	1.0
0.5009	0.34	600	0.2709	0.2162
0.2056	0.5	900	0.1934	0.1602
0.1648	0.67	1200	0.1576	0.1306
0.1922	0.84	1500	0.1358	0.1114
0.093	1.01	1800	0.1277	0.1035
0.0652	1.18	2100	0.1251	0.1005
0.0848	1.35	2400	0.1188	0.0964
0.0706	1.51	2700	0.1091	0.0905
0.0846	1.68	3000	0.1018	0.0840
0.0684	1.85	3300	0.0978	0.0809

Framework versions

Transformers 4.15.0
Pytorch 1.9.1
Datasets 1.18.0
Tokenizers 0.10.3

anjulRajendraSharma/wavlm-base-libri-clean-100

wavlm-libri-clean-100h-base

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

anjulRajendraSharma/
wavlm-base-libri-clean-100