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wav2vec2-speechcommonds-kws

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

  • Loss: 0.0613
  • Accuracy: 0.9855

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: 42
  • 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

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0871 1.0 741 0.3374 0.9810
0.5168 2.0 1482 0.1022 0.9866
0.4113 3.0 2223 0.0766 0.9853
0.3622 4.0 2964 0.0670 0.9859
0.3454 5.0 3705 0.0613 0.9855

Framework versions

  • Transformers 4.36.1
  • Pytorch 2.1.1
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Dataset used to train EWCH/wav2vec2-speechcommonds-kws

Evaluation results