VMadalina/whisper-medium-news-augmented2

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Whisper Large Ro - VM3

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

• —Loss: 0.2002
• —Wer: 13.6187
• —Cer: 5.2529

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: 5e-06
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 32
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 300
• —training_steps: 8000
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.50.1
• —Pytorch 2.6.0+cu124
• —Datasets 2.19.1
• —Tokenizers 0.21.1