whisper-large-v2-aph_2 – AI Model by npallewela | AlphaNeural AI

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npallewela/
whisper-large-v2-aph_2

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automatic-speech-recognition

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openai/whisper-large-v2

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Whisper large v2 aphasia - 4000

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: 0.4831
Wer Ortho: 25.1008
Wer: 24.4105

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
0.3891	0.0943	400	0.5067	27.3569	26.6046
0.3924	0.1886	800	0.5045	26.7300	26.1199
0.3608	0.2830	1200	0.4992	25.7602	25.1610
0.4125	0.3773	1600	0.4921	25.5888	24.9726
0.3768	0.4716	2000	0.4831	25.1008	24.4105

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1