This model is a fine-tuned version of openai/whisper-small.en on the Medicines ASR Dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.0001
Wer: 0.0

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: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.035	1.0905	1000	0.0312	6.5282
0.0042	2.1810	2000	0.0018	0.5935
0.0083	3.2715	3000	0.0007	0.0
0.0003	4.3621	4000	0.0001	0.0
0.0002	5.4526	5000	0.0001	0.0

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2

yezarniko/pharmacy-whisper-en-v2

Pharmacy ASR Whisper Base Model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

yezarniko/
pharmacy-whisper-en-v2