wav2vec2-random

This model is a fine-tuned version of patrickvonplaten/wav2vec2-base-random on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

• Loss: 3.1593
• Wer: 0.8364

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: 32
• eval_batch_size: 1
• 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: 20.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.9043	0.69	100	2.9683	1.0
2.8537	1.38	200	2.9281	0.9997
2.7803	2.07	300	2.7330	0.9999
2.6806	2.76	400	2.5792	1.0
2.4136	3.45	500	2.4327	0.9948
2.1682	4.14	600	2.3508	0.9877
2.2577	4.83	700	2.2176	0.9773
2.355	5.52	800	2.1753	0.9542
1.8588	6.21	900	2.0650	0.8851
1.6831	6.9	1000	2.0109	0.8618
1.888	7.59	1100	1.9660	0.8418
2.0066	8.28	1200	1.9847	0.8531
1.7044	8.97	1300	1.9760	0.8527
1.3168	9.66	1400	2.0708	0.8327
1.2143	10.34	1500	2.0601	0.8419
1.6189	11.03	1600	2.0960	0.8299
1.13	11.72	1700	2.2540	0.8408
0.8001	12.41	1800	2.4260	0.8306
0.7769	13.1	1900	2.4182	0.8445
1.2165	13.79	2000	2.3666	0.8284
0.8026	14.48	2100	2.7118	0.8662
0.5148	15.17	2200	2.7957	0.8526
0.4921	15.86	2300	2.8244	0.8346
0.7629	16.55	2400	2.8944	0.8370
0.5762	17.24	2500	3.0335	0.8367
0.4076	17.93	2600	3.0776	0.8358
0.3395	18.62	2700	3.1572	0.8261
0.4862	19.31	2800	3.1319	0.8414
0.5061	20.0	2900	3.1593	0.8364

Framework versions

• Transformers 4.12.0.dev0
• Pytorch 1.8.1
• Datasets 1.14.1.dev0
• Tokenizers 0.10.3