This model is a fine-tuned version of openai/whisper-small on the medical-speech-transcription-and-intent dataset. It achieves the following results on the evaluation set:

Loss: 0.0931
Wer: 3.9012

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: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0165	3.3898	1000	0.0971	4.7860
0.0012	6.7797	2000	0.0905	4.1425
0.0001	10.1695	3000	0.0930	4.0138
0.0001	13.5593	4000	0.0931	3.9012

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.20.3

jithuj12344321/whisper-small-en

Whisper Small En - Jithu J

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jithuj12344321/
whisper-small-en