This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3078
Wer: 29.9382

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 OptimizerNames.ADAMW_TORCH 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: 500
training_steps: 6000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1113	1.0152	2000	0.4020	38.7338
0.0554	2.0305	4000	0.3469	35.0827
0.0204	3.0457	6000	0.3078	29.9382

Framework versions

Transformers 4.52.4
Pytorch 2.7.1+cu118
Datasets 3.6.0
Tokenizers 0.21.1