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CLEAR-Global/w2v-bert-2.0-luo_cv_fleurs_19h-v3

sourceHugging Facemitupdated 1y agoView on Hugging Face
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w2v-bert-2.0-luocvfleurs_19h-v3

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the CLEAR-GLOBAL/LUO_19H - NA dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2850
  • —Wer: 0.3100
  • —Cer: 0.0950

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: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 64
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.05
  • —training_steps: 100000
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWerCer
0.91856.493510000.80560.68170.2146
0.333812.987020000.41230.40700.1262
0.188819.480530000.30170.34920.1042
0.103225.974040000.28510.31000.0946
0.054132.467550000.31720.30600.0946
0.028438.961060000.31640.28970.0912
0.014545.454570000.34780.28790.0904
0.017651.948180000.39710.31130.0933
0.005158.441690000.41490.30510.0905

Framework versions

  • —Transformers 4.48.1
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.5.0
  • —Tokenizers 0.21.1