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Jethuestad/
dat259-cv_en-wav2vec2

Name: dat259-cv_en-wav2vec2
Availability: InStock

transformers

pytorch

wav2vec2

automatic-speech-recognition

generated_from_trainer

common_voice_1_0

apache-2.0

endpoints_compatible

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dat259-cv_en-wav2vec2

This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:

Loss: 1.4286
Wer: 0.5339

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.383	1.32	200	3.0312	1.0
2.7346	2.63	400	2.0207	0.9413
0.8772	3.95	600	1.3528	0.6911
0.4718	5.26	800	1.1830	0.6135
0.3209	6.58	1000	1.2242	0.5856
0.2556	7.89	1200	1.3165	0.5894
0.2055	9.21	1400	1.3716	0.5708
0.18	10.53	1600	1.2709	0.5702
0.1497	11.84	1800	1.4300	0.5526
0.126	13.16	2000	1.3852	0.5507
0.1145	14.47	2200	1.3893	0.5489
0.101	15.79	2400	1.4051	0.5431
0.091	17.11	2600	1.4103	0.5399
0.0793	18.42	2800	1.3968	0.5324
0.0746	19.74	3000	1.4286	0.5339

Framework versions

Transformers 4.21.1
Pytorch 1.12.1+cu102
Datasets 2.4.0
Tokenizers 0.12.1

Jethuestad/dat259-cv_en-wav2vec2

dat259-cv_en-wav2vec2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Jethuestad/
dat259-cv_en-wav2vec2