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

Loss: 0.1775
Cer: 11.0108
Wer: 15.8491

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: 3e-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: 950
training_steps: 9500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
0.3642	0.8565	1000	0.3042	88.0089	85.6774
0.1563	1.7126	2000	0.2370	56.9486	47.3565
0.0783	2.5687	3000	0.2043	16.7586	23.7618
0.0305	3.4248	4000	0.1935	21.0814	25.2930
0.0164	4.2809	5000	0.1843	19.5680	21.6927
0.01	5.1370	6000	0.1823	13.3842	17.4606
0.0086	5.9936	7000	0.1792	22.1973	24.9455
0.003	6.8497	8000	0.1787	12.8683	17.4494
0.0016	7.7058	9000	0.1775	11.0108	15.8491

Framework versions

Transformers 4.53.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

yoona-J/ASR_Whisper_Peripheral_Neuropathy

ASR_Whisper_Peripheral_Neuropathy

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

yoona-J/
ASR_Whisper_Peripheral_Neuropathy