whisper-large-v2-aph_3 – AI Model by npallewela | AlphaNeural AI

You can deploy this model and start earning money today!

npallewela/
whisper-large-v2-aph_3

like

0

automatic-speech-recognition

generated_from_trainer

openai/whisper-large-v2

endpoints_compatible

Views

No views yet

Whisper large v2 aphasia - 6000

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4907
Wer Ortho: 24.2469
Wer: 23.4976

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-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.282	0.0943	400	0.4916	25.3333	24.6931
0.2971	0.1886	800	0.4977	24.6683	24.0689
0.2685	0.2830	1200	0.4947	24.4548	23.8568
0.2981	0.3773	1600	0.4968	24.8230	24.2489
0.3023	0.4716	2000	0.4907	24.2469	23.4976

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1