pidgin-wav2vec2-xlsr53

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the Nigerian Pidgin dataset. It achieves the following results on the evaluation set:

• Loss: 0.6907
• Wer: 0.3161 (val)

Model description

to be updated

Intended uses & limitations

to be updated

Training and evaluation data

to be updated

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 3407
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• 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
6.604	1.48	500	3.0540	1.0
3.0176	2.95	1000	3.0035	1.0
2.1071	4.43	1500	1.0811	0.6289
1.1143	5.91	2000	0.8348	0.5017
0.8501	7.39	2500	0.7707	0.4352
0.7272	8.86	3000	0.7410	0.4075
0.6038	10.34	3500	0.6283	0.3850
0.5334	11.82	4000	0.6356	0.3701
0.4645	13.29	4500	0.6243	0.3657
0.4251	14.77	5000	0.6838	0.3492
0.3801	16.25	5500	0.6619	0.3445
0.3636	17.73	6000	0.6945	0.3360
0.3366	19.2	6500	0.6108	0.3340
0.3146	20.68	7000	0.6511	0.3273
0.3003	22.16	7500	0.6815	0.3253
0.2783	23.63	8000	0.6761	0.3215
0.2601	25.11	8500	0.6762	0.3187
0.2528	26.59	9000	0.6687	0.3194
0.2409	28.06	9500	0.7064	0.3163
0.2359	29.54	10000	0.6907	0.3161

Framework versions

• Transformers 4.37.2
• Pytorch 2.0.1+cu117
• Datasets 2.12.0
• Tokenizers 0.15.2