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: 0.4319
Wer: 38.3891

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: 200
training_steps: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5823	0.7194	600	0.5640	48.7739
0.3761	1.4388	1200	0.4798	41.6642
0.2204	2.1583	1800	0.4506	39.9044
0.4718	2.8777	2400	0.4322	39.9642
0.2857	3.5971	3000	0.4319	38.3891

Framework versions

Transformers 5.14.1
Pytorch 2.12.0+cu130
Datasets 5.0.0
Tokenizers 0.22.2

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

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