Tsedee/whisper-large-v2-mn-commercial-v2

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whisper-large-v2-mn-commercial-v2

This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3590
• —Wer: 0.456
• —Cer: 0.1536

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: 16
• —evalbatchsize: 4
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —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: 50
• —num_epochs: 2
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —PEFT 0.18.1
• —Transformers 4.46.3
• —Pytorch 2.4.1+cu124
• —Datasets 3.6.0
• —Tokenizers 0.20.3