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wav2vec2-base-finetuned-ks

This model was trained from scratch on the superb dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0799
  • Accuracy: 0.9812

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: 3e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.222 1.0 199 0.1320 0.9748
0.1763 2.0 399 0.1063 0.9762
0.1502 3.0 599 0.0858 0.9798
0.1234 4.0 799 0.0855 0.9804
0.1402 4.98 995 0.0799 0.9812

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Dataset used to train selinawisco/wav2vec2-base-finetuned-ks

Evaluation results