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:

Loss: 0.2555
Wer: 13.1072

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: 6.25e-06
train_batch_size: 32
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: 800
training_steps: 4500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.234	0.2	900	0.2541	13.2906
0.2239	0.4	1800	0.2514	13.5961
0.1413	1.1	2700	0.2544	13.3211
0.0899	1.3	3600	0.2585	13.1989
0.1138	1.5	4500	0.2555	13.1072

Framework versions

Transformers 4.51.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

xbilek25/whisper-medium-en-cv-1.5

Whisper medium v1.5 - 100h

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

xbilek25/
whisper-medium-en-cv-1.5