Serialtechlab / w2v-bert-2.0-dhivehi-cv

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Model's Last Updated: December 28 2025

Introduction of w2v-bert-2.0-dhivehi-cv

Model Details of w2v-bert-2.0-dhivehi-cv

w2v Bert 2.0 Dv - alakxender

This model is a fine-tuned version of alakxender/w2v-bert-2.0-dhivehi-cv on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3580
  • Wer: 0.4591
Model description

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Intended uses & limitations

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Training and evaluation data

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Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
1.9272 3.8961 300 0.3712 0.5096
0.1846 7.7922 600 0.3580 0.4591
Framework versions
  • Transformers 4.41.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1

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