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wav2vec2-large-xls-r-may23-luganda-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7210
  • Wer: 0.5021

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: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0539 7.77 400 0.6641 0.5738
0.0725 15.53 800 0.6735 0.5932
0.058 23.3 1200 0.6754 0.5751
0.0517 31.07 1600 0.6591 0.5901
0.0437 38.83 2000 0.7140 0.5658
0.0366 46.6 2400 0.7154 0.5602
0.0295 54.37 2800 0.6942 0.5140
0.0251 62.14 3200 0.7095 0.5204
0.0191 69.9 3600 0.7459 0.5267
0.0157 77.67 4000 0.6825 0.5155
0.0126 85.44 4400 0.7197 0.5135
0.0098 93.2 4800 0.7210 0.5021

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Datasets 1.18.3
  • Tokenizers 0.13.3
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Dataset used to train Gemmar/wav2vec2-large-xls-r-may23-luganda-colab

Evaluation results