This model is a fine-tuned version of openai/whisper-medium on the Physician Dictation GPT 4 Turbo dataset. It achieves the following results on the evaluation set:

Loss: 0.1660
Wer: 5.3497

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: 8
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 8500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0143	3.9683	500	0.1068	4.9948
0.0023	7.9365	1000	0.1287	5.0757
0.0026	11.9048	1500	0.1254	4.9409
0.0003	15.8730	2000	0.1298	4.7298
0.001	19.8413	2500	0.1312	5.0173
0.0001	23.8095	3000	0.1405	5.2374
0.0001	27.7778	3500	0.1454	4.9903
0.0001	31.7460	4000	0.1497	5.2104
0.0	35.7143	4500	0.1531	5.1835
0.0	39.6825	5000	0.1558	5.1431
0.0	43.6508	5500	0.1581	5.1296
0.0	47.6190	6000	0.1601	5.1700
0.0	51.5873	6500	0.1619	5.1925
0.0	55.5556	7000	0.1635	5.2329
0.0	59.5238	7500	0.1648	5.2733
0.0	63.4921	8000	0.1656	5.3362
0.0	67.4603	8500	0.1660	5.3497

Framework versions

Transformers 4.40.2
Pytorch 2.0.1+cu117
Datasets 2.19.1
Tokenizers 0.19.1

sujithvemi/whisper-medium-physician-dictation-gpt-4-turbo

Whisper Large v3 Physician Dictation GPT 4 turbo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sujithvemi/
whisper-medium-physician-dictation-gpt-4-turbo