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wav2vec2-base-ft-keyword-spotting

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

  • Loss: 0.0804
  • Accuracy: 0.9829

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: 32
  • eval_batch_size: 32
  • seed: 0
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5081 1.0 399 0.3587 0.9698
0.2772 2.0 798 0.1273 0.9763
0.1748 3.0 1197 0.0957 0.9796
0.1407 4.0 1597 0.0804 0.9829
0.1233 5.0 1995 0.0774 0.9825

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.0
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Finetuned from

Dataset used to train zongxiao/wav2vec2-base-ft-keyword-spotting

Evaluation results