librispeech-100h-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: 0.0955
• Wer: 0.0345

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: 24
• 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: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.8277	0.42	500	2.9071	1.0
2.0261	0.84	1000	0.3060	0.2496
0.2181	1.26	1500	0.1172	0.0873
0.1255	1.68	2000	0.0894	0.0637
0.0971	2.1	2500	0.0821	0.0560
0.078	2.52	3000	0.0751	0.0500
0.0706	2.94	3500	0.0721	0.0456
0.0609	3.36	4000	0.0755	0.0464
0.0572	3.78	4500	0.0705	0.0431
0.0528	4.2	5000	0.0715	0.0423
0.0481	4.62	5500	0.0691	0.0403
0.0471	5.04	6000	0.0743	0.0401
0.0412	5.46	6500	0.0757	0.0399
0.0416	5.88	7000	0.0688	0.0378
0.0391	6.3	7500	0.0704	0.0383
0.0367	6.72	8000	0.0742	0.0387
0.0349	7.14	8500	0.0732	0.0388
0.033	7.56	9000	0.0719	0.0374
0.0327	7.98	9500	0.0750	0.0369
0.0292	8.4	10000	0.0734	0.0368
0.0303	8.82	10500	0.0733	0.0365
0.0283	9.24	11000	0.0766	0.0357
0.0269	9.66	11500	0.0761	0.0350
0.0268	10.08	12000	0.0802	0.0359
0.0245	10.42	12500	0.0758	0.0354
0.023	10.84	13000	0.0775	0.0349
0.0186	11.26	13500	0.0817	0.0355
0.0176	11.68	14000	0.0853	0.0354
0.0163	12.1	14500	0.0880	0.0347
0.0156	12.52	15000	0.0864	0.0357
0.0141	12.94	15500	0.0897	0.0355
0.0134	13.36	16000	0.0915	0.0349
0.013	13.78	16500	0.0928	0.0350
0.0097	13.42	17000	0.0955	0.0345

Framework versions

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