whisper-small-sm – AI Model by Bedru | AlphaNeural AI

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Bedru/
whisper-small-sm

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automatic-speech-recognition

generated_from_trainer

openai/whisper-small

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Whisper-Small-am-v11

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

Loss: 0.6920
Wer: 183.3625

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-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
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: 100
training_steps: 400
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.2222	50	1.1042	338.7729
1.2376	0.4444	100	0.9183	301.9761
1.2376	0.6667	150	0.8419	213.0040
0.7542	0.8889	200	0.7960	188.3506
0.7542	1.1111	250	0.7673	186.8685
0.676	1.3333	300	0.7388	193.2430
0.676	1.5556	350	0.7148	188.5100
0.6401	1.7778	400	0.6920	183.3625

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.1
Tokenizers 0.21.1