whisper-large-v2-aphasia1 – AI Model by npallewela | AlphaNeural AI

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whisper-large-v2-aphasia1

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automatic-speech-recognition

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openai/whisper-large-v2

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Whisper large v2 aphasia - Nuwan

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: 0.5667
Wer Ortho: 32.9754
Wer: 32.0758

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: 100
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.7049	0.0472	200	0.7395	41.4881	40.2489
0.606	0.0943	400	0.6397	33.2373	32.4595
0.5243	0.1415	600	0.6069	36.2108	35.3199
0.5454	0.1886	800	0.5835	34.2110	33.4666
0.5021	0.2358	1000	0.5667	32.9754	32.0758

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1