This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 sw dataset. It achieves the following results on the evaluation set:

Loss: 0.6442
Wer: 23.7246

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2694	1.07	1000	0.5438	26.8354
0.2306	3.02	2000	0.5081	23.9231
0.0467	4.09	3000	0.5648	24.4085
0.0239	6.03	4000	0.5994	23.8634
0.0123	7.1	5000	0.6442	23.7246

Framework versions

Transformers 4.30.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.12.1.dev0
Tokenizers 0.13.3

DuniaComGroup/whisper-small-sw

Whisper Small Swahili

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DuniaComGroup/
whisper-small-sw