This model is a fine-tuned version of openai/whisper-base on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set:

Loss: 0.4155
Wer: 36.5641

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: 16
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 450
training_steps: 4500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8726	0.5995	500	0.6528	52.2635
0.3447	1.1990	1000	0.5072	43.9481
0.4441	1.7986	1500	0.4546	41.4442
0.2473	2.3981	2000	0.4379	40.0185
0.3866	2.9976	2500	0.4269	40.1108
0.2246	3.5971	3000	0.4198	37.4114
0.3989	4.1966	3500	0.4188	37.5608
0.2698	4.7962	4000	0.4135	37.9871
0.1525	5.3957	4500	0.4155	36.5641

Framework versions

Transformers 5.14.1
Pytorch 2.13.0+cu130
Datasets 5.0.1
Tokenizers 0.22.2

CasperMuz/whisper-base-sna-cleaned-s2s-m-curriculum-4.5k

Whisper Base Shona - S2S-M Curriculum 3000 steps

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

CasperMuz/
whisper-base-sna-cleaned-s2s-m-curriculum-4.5k