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

Cer: 4.0149
Wer: 14.0500
Loss: 0.1453

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: 16
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: warmup_stable_decay
lr_scheduler_warmup_steps: 1025
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Cer	Wer	Validation Loss
0.1709	1.0	2052	6.2976	22.0505	0.1529
0.1076	2.0	4104	5.5274	18.8083	0.1377
0.0509	3.0	6156	4.7389	16.4986	0.1399
0.0223	4.0	8208	4.3180	14.9002	0.1409
0.004	5.0	10260	4.0149	14.0500	0.1453

Framework versions

Transformers 4.52.4
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.4

SmartWhatt/rangsitra-whisper-md-cv

Rangsitra Whisper

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

SmartWhatt/
rangsitra-whisper-md-cv