wandererupak/whisper-small-n-demo-new-data-final

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Whisper Small N - Final

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

• —eval_loss: 0.6699
• —eval_wer: 50.2477
• —eval_cer: 17.2383
• —eval_runtime: 162.322
• —evalsamplesper_second: 2.169
• —evalstepsper_second: 0.271
• —epoch: 13.9235
• —step: 2464

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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 16
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 0.1
• —num_epochs: 20
• —mixedprecisiontraining: Native AMP

Framework versions

• —Transformers 5.1.0
• —Pytorch 2.9.0+cu126
• —Datasets 4.5.0
• —Tokenizers 0.22.2