wsj0-full-supervised

This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0623
• Wer: 0.0343

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: 12
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.517	0.86	500	2.9475	1.0
2.2387	1.72	1000	0.4004	0.3498
0.3081	2.57	1500	0.1362	0.1159
0.1744	3.43	2000	0.1125	0.0929
0.1285	4.29	2500	0.0894	0.0727
0.1015	5.15	3000	0.0852	0.0642
0.0811	6.0	3500	0.0789	0.0614
0.0748	6.86	4000	0.0746	0.0529
0.0639	7.72	4500	0.0714	0.0481
0.0606	8.58	5000	0.0698	0.0489
0.0525	9.43	5500	0.0747	0.0464
0.0489	10.29	6000	0.0594	0.0396
0.0419	11.15	6500	0.0600	0.0359
0.0414	12.01	7000	0.0612	0.0412
0.0383	12.86	7500	0.0676	0.0392
0.0352	13.72	8000	0.0626	0.0388
0.034	14.58	8500	0.0699	0.0372
0.0309	15.44	9000	0.0807	0.0420
0.0295	16.3	9500	0.0796	0.0396
0.0273	17.15	10000	0.0716	0.0376
0.0271	18.01	10500	0.0657	0.0384
0.0251	18.87	11000	0.0585	0.0351
0.024	19.73	11500	0.0557	0.0347
0.0252	20.58	12000	0.0609	0.0327
0.0231	21.44	12500	0.0720	0.0368
0.0202	22.3	13000	0.0625	0.0343
0.0195	23.16	13500	0.0635	0.0372
0.0201	24.01	14000	0.0582	0.0335
0.0183	24.87	14500	0.0562	0.0343
0.0183	25.73	15000	0.0629	0.0335
0.0175	26.59	15500	0.0593	0.0323
0.017	27.44	16000	0.0631	0.0339
0.0162	28.3	16500	0.0597	0.0335
0.0169	29.16	17000	0.0623	0.0343

Framework versions

• Transformers 4.14.1
• Pytorch 1.10.2
• Datasets 1.18.2
• Tokenizers 0.10.3