anuragshas/wav2vec2-xls-r-300m-mr-cv8-with-lm

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset. It achieves the following results on the evaluation set:

Loss: 0.6693
Wer: 0.5921

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: 7.5e-05
train_batch_size: 32
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: 2000
num_epochs: 500.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.9504	18.18	400	4.6730	1.0
3.3766	36.36	800	3.3464	1.0
3.1128	54.55	1200	3.0177	0.9980
1.7966	72.73	1600	0.8733	0.8039
1.4085	90.91	2000	0.5555	0.6458
1.1731	109.09	2400	0.4930	0.6438
1.0271	127.27	2800	0.4780	0.6093
0.9045	145.45	3200	0.4647	0.6578
0.807	163.64	3600	0.4505	0.5925
0.741	181.82	4000	0.4746	0.6025
0.6706	200.0	4400	0.5004	0.5844
0.6186	218.18	4800	0.4984	0.5997
0.5508	236.36	5200	0.5298	0.5636
0.5123	254.55	5600	0.5410	0.5110
0.4623	272.73	6000	0.5591	0.5383
0.4281	290.91	6400	0.5775	0.5600
0.4045	309.09	6800	0.5924	0.5580
0.3651	327.27	7200	0.5671	0.5684
0.343	345.45	7600	0.6083	0.5945
0.3085	363.64	8000	0.6243	0.5728
0.2941	381.82	8400	0.6245	0.5580
0.2735	400.0	8800	0.6458	0.5804
0.262	418.18	9200	0.6566	0.5824
0.2578	436.36	9600	0.6558	0.5965
0.2388	454.55	10000	0.6598	0.5993
0.2328	472.73	10400	0.6700	0.6041
0.2286	490.91	10800	0.6684	0.5957

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2+cu102
Datasets 1.18.4.dev0
Tokenizers 0.11.0