This model is a fine-tuned version of EYEDOL/whisper-tiny-yoruba on the EYEDOL/naija-voices-yoruba-split_0-1 dataset. It achieves the following results on the evaluation set:

Loss: 0.8526
Wer Ortho: 0.7773
Wer: 0.7006

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: 1e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 0.1
num_epochs: 12
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
1.7353	1.0	583	0.8680	0.9448	0.8654
1.6436	2.0	1166	0.8494	0.8213	0.7490
1.5173	3.0	1749	0.8319	0.8237	0.7470
1.4143	4.0	2332	0.8215	0.7845	0.7128
1.3252	5.0	2915	0.8135	0.8788	0.7910
1.2425	6.0	3498	0.8106	0.7988	0.7224
1.1664	7.0	4081	0.8118	0.8508	0.7635
1.0950	8.0	4664	0.8156	0.7628	0.6813
1.0273	9.0	5247	0.8191	0.7867	0.7204
0.9611	10.0	5830	0.8292	0.7736	0.6948
0.8975	11.0	6413	0.8353	0.8007	0.7126
0.8363	12.0	6996	0.8526	0.7773	0.7006

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2