p29ris/whisper-torgo-uaspeech-tiny

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whisper-torgo-uaspeech-tiny

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:

• —eval_loss: 0.0934
• —eval_wer: 0.223
• —eval_cer: 0.1546
• —eval_f1: 0.7919
• —eval_runtime: 112.9071
• —evalsamplesper_second: 8.857
• —evalstepsper_second: 1.107
• —epoch: 2.6649
• —step: 1500

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: 2e-05
• —trainbatchsize: 4
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 16
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —training_steps: 3000
• —mixedprecisiontraining: Native AMP

Framework versions

• —Transformers 4.53.3
• —Pytorch 2.6.0+cu124
• —Datasets 4.1.1
• —Tokenizers 0.21.2