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Jethuestad/
dat259-wav2vec2-en2

Name: dat259-wav2vec2-en2
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-wav2vec2-en2

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: 1.4036
Wer: 0.5090

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: 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: 300
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.4355	1.82	200	3.0307	1.0
2.1744	3.64	400	1.5661	0.7449
0.5535	5.45	600	1.3005	0.5914
0.3248	7.27	800	1.2481	0.5690
0.2297	9.09	1000	1.2810	0.5366
0.18	10.91	1200	1.3481	0.5378
0.1499	12.73	1400	1.3124	0.5350
0.1283	14.55	1600	1.3668	0.5161
0.1089	16.36	1800	1.3833	0.5109
0.0973	18.18	2000	1.3876	0.5075
0.0897	20.0	2200	1.4036	0.5090

Framework versions

Transformers 4.21.1
Pytorch 1.12.1+cu102
Datasets 2.4.0
Tokenizers 0.12.1

Jethuestad/dat259-wav2vec2-en2

dat259-wav2vec2-en2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Jethuestad/
dat259-wav2vec2-en2