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Wave2Vec2-Bert2.0 - Kiran Pantha

This model is a fine-tuned version of kiranpantha/w2v-bert-2.0-nepali on the OpenSLR54 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4052
  • Wer: 0.4302
  • Cer: 0.1029

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.7515 0.15 300 0.4814 0.4911 0.1183
0.6554 0.3 600 0.5699 0.5382 0.1385
0.6723 0.45 900 0.5463 0.5401 0.1395
0.6635 0.6 1200 0.5244 0.5043 0.1250
0.6132 0.75 1500 0.4725 0.4831 0.1184
0.5786 0.9 1800 0.4620 0.4702 0.1147
0.5639 1.05 2100 0.4810 0.4668 0.1140
0.4863 1.2 2400 0.4639 0.4766 0.1151
0.4784 1.35 2700 0.4527 0.4611 0.1108
0.456 1.5 3000 0.4229 0.4458 0.1089
0.4613 1.65 3300 0.4460 0.4478 0.1095
0.4506 1.8 3600 0.4166 0.4413 0.1047
0.4369 1.95 3900 0.4052 0.4302 0.1029

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Evaluation results