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patrickvonplaten/
wavlm-libri-clean-100h-large

Name: wavlm-libri-clean-100h-large
Availability: InStock

automatic-speech-recognition

librispeech_asr

generated_from_trainer

wavlm_libri_finetune

endpoints_compatible

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wavlm-libri-clean-100h-large

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

Loss: 0.0601
Wer: 0.0491

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: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8069	0.34	300	0.7510	0.5809
0.2483	0.67	600	0.2023	0.1929
0.1033	1.01	900	0.1123	0.1028
0.0742	1.35	1200	0.0858	0.0771
0.057	1.68	1500	0.0722	0.0663
0.0421	2.02	1800	0.0682	0.0582
0.0839	2.35	2100	0.0630	0.0534
0.0307	2.69	2400	0.0603	0.0508

Framework versions

Transformers 4.15.0.dev0
Pytorch 1.9.0+cu111
Datasets 1.16.2.dev0
Tokenizers 0.10.3

patrickvonplaten/wavlm-libri-clean-100h-large

wavlm-libri-clean-100h-large

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

patrickvonplaten/
wavlm-libri-clean-100h-large