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luganda_wav2vec2_ctc_tokenizer

This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_7_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5588
  • Wer: 0.5609

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: 0.0001
  • train_batch_size: 32
  • 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: 1000
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.1365 2.4 500 1.9598 1.0
0.5695 4.81 1000 0.5853 0.7329
0.176 7.21 1500 0.5381 0.6747
0.0845 9.62 2000 0.5128 0.6270
0.0424 12.02 2500 0.4651 0.6014
0.0127 14.42 3000 0.5395 0.6049
-0.0063 16.83 3500 0.5169 0.5842
-0.0212 19.23 4000 0.4990 0.5833
-0.0336 21.63 4500 0.5318 0.5680
-0.0424 24.04 5000 0.5465 0.5702
-0.0495 26.44 5500 0.5541 0.5637
-0.0565 28.85 6000 0.5588 0.5609

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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Evaluation results