razhan/whisper-base-glk

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whisper-base-hac-telegram

This model is a fine-tuned version of openai/whisper-base on the razhan/DOLMA-speech gilaki dataset. It achieves the following results on the evaluation set:

• —Loss: 2.6806
• —Wer: 1.0472
• —Cer: 0.5468

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: 256
• —evalbatchsize: 128
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 2
• —totaltrainbatch_size: 512
• —totalevalbatch_size: 256
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 100
• —num_epochs: 5.0
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.49.0.dev0
• —Pytorch 2.6.0+cu124
• —Datasets 3.2.0
• —Tokenizers 0.21.0