itsally/Dataset

Fine Tune Whisper on People Speech

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

• Loss: 0.5068
• Wer: 14.7846

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: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0071	2.0	100	0.5080	14.2950
0.006	4.0	200	0.4859	14.1645
0.0012	6.0	300	0.4997	14.3603
0.0002	8.0	400	0.5017	14.4582
0.0005	10.0	500	0.5068	14.7846

Framework versions

• Transformers 4.52.0
• Pytorch 2.9.0+cu126
• Datasets 4.4.1
• Tokenizers 0.21.4