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wav2vec2-base-TPU-cv-fine-tune-2

This model is a fine-tuned version of jiobiala24/wav2vec2-base-TPU-cv-fine-tune on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6051
  • Wer: 0.5484

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: 30

Training results

Training Loss Epoch Step Validation Loss Wer
0.522 6.45 400 1.2550 0.5649
0.2874 12.9 800 1.4235 0.6054
0.152 19.35 1200 1.5743 0.5806
0.0857 25.8 1600 1.6051 0.5484

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.13.3
  • Tokenizers 0.10.3
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Dataset used to train jiobiala24/wav2vec2-base-checkpoint-2