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

Loss: 0.9135
Wer: 32.0882

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: 48
eval_batch_size: 32
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: 42
training_steps: 420
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0	0	1.5148	34.2009
0.565	0.2	84	0.9564	29.4856
0.4559	0.4	168	0.9294	29.7918
0.2937	1.1833	252	0.9136	28.1384
0.262	1.3833	336	0.9206	28.3527
0.2024	2.1667	420	0.9135	32.0882

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

xbilek25/wme_30s_Static_atWall

wme_30s_Static_atWall

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

xbilek25/
wme_30s_Static_atWall