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Dovud-Asadov/whisper-uzbek-multi-dataset

sourceHugging Facemitupdated 11mo agoView on Hugging Face
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whisper-uzbek-multi-dataset

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2215
  • —Wer: 24.5188

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: 4
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 8
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 3
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.42190.157710000.420337.8390
0.34670.315420000.356835.5245
0.31520.473130000.314631.8340
0.27670.630940000.298431.7955
0.29080.788650000.284130.2510
0.25890.946360000.270228.5905
0.19411.103970000.264828.2867
0.17781.261780000.261327.8530
0.20721.419490000.253827.3528
0.19441.5771100000.246626.9360
0.18891.7348110000.241726.5371
0.17781.8925120000.236125.7168
0.13842.0502130000.234525.6473
0.12872.2079140000.234525.8865
0.13352.3656150000.231425.3250
0.13422.5233160000.228624.9627
0.1292.6810170000.225524.7568
0.12132.8387180000.223224.5562
0.12552.9965190000.221524.5188

Framework versions

  • —Transformers 4.57.1
  • —Pytorch 2.9.0+cu130
  • —Datasets 4.2.0
  • —Tokenizers 0.22.1