This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_7_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.7622
Wer: 0.5422

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: 48
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: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.2675	3.6	500	1.9999	0.9999
0.5754	7.19	1000	0.6976	0.7050
0.231	10.79	1500	0.6153	0.6440
0.1557	14.39	2000	0.6581	0.6130
0.1221	17.99	2500	0.6718	0.6063
0.1013	21.58	3000	0.6711	0.5934
0.0871	25.18	3500	0.6728	0.5731
0.0751	28.78	4000	0.6729	0.5726
0.0666	32.37	4500	0.6884	0.5689
0.0604	35.97	5000	0.7452	0.5609
0.0543	39.57	5500	0.7302	0.5616
0.0488	43.17	6000	0.7414	0.5480
0.0448	46.76	6500	0.7662	0.5560
0.042	50.36	7000	0.7629	0.5433
0.038	53.96	7500	0.7582	0.5479
0.0353	57.55	8000	0.7622	0.5422

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2

dmusingu/luganda_wav2vec2_ctc

luganda_wav2vec2_ctc

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dmusingu/
luganda_wav2vec2_ctc