This model is a fine-tuned version of openai/whisper-large-v3 on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set:

Loss: 0.4129
Wer: 36.5071

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
13.4173	0.5996	500	0.6003	49.4012
5.2073	1.1991	1000	0.4735	39.8392
7.1774	1.7986	1500	0.4383	38.8371
4.4790	2.3981	2000	0.4283	37.0747
7.1915	2.9977	2500	0.4226	37.4413
4.8270	3.5972	3000	0.4157	36.6130
7.9870	4.1967	3500	0.4197	36.1432
6.2143	4.7962	4000	0.4134	36.4745
3.6004	5.3957	4500	0.4129	36.5071

Framework versions

Transformers 5.14.1
Pytorch 2.13.0+cu130
Datasets 5.0.1
Tokenizers 0.22.2

CasperMuz/whisper-large-v3-sna-cleaned-s2s-m-curriculum-4.5k

Whisper Large-v3 Shona - S2S-M Curriculum 4500 steps

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

CasperMuz/
whisper-large-v3-sna-cleaned-s2s-m-curriculum-4.5k