whisper-large-v2-aph_1 – AI Model by npallewela | AlphaNeural AI

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npallewela/
whisper-large-v2-aph_1

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automatic-speech-recognition

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openai/whisper-large-v2

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Whisper large v2 aphasia - 2000

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: 0.5148
Wer Ortho: 27.2934
Wer: 26.6452

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
lr_scheduler_warmup_steps: 200
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.62	0.0943	400	0.6506	35.1514	34.0594
0.5504	0.1886	800	0.5892	33.9968	33.1434
0.4954	0.2830	1200	0.5583	28.8726	28.1999
0.562	0.3773	1600	0.5348	28.7116	28.1011
0.479	0.4716	2000	0.5148	27.2934	26.6452

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1