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metadata
tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - superb
metrics:
  - accuracy
model-index:
  - name: trillsson3-ft-keyword-spotting-13
    results: []

trillsson3-ft-keyword-spotting-13

This model is a fine-tuned version of vumichien/nonsemantic-speech-trillsson3 on the superb dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3085
  • Accuracy: 0.9153

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: 32
  • seed: 0
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.8064 1.0 798 0.9359 0.6403
0.8601 2.0 1596 0.4832 0.8528
0.7585 3.0 2394 0.3952 0.8854
0.7026 4.0 3192 0.3623 0.9050
0.6924 5.0 3990 0.3456 0.9035
0.6816 6.0 4788 0.3405 0.9006
0.6461 7.0 5586 0.3384 0.9004
0.6697 8.0 6384 0.3272 0.9045
0.6575 9.0 7182 0.3237 0.9109
0.6634 10.0 7980 0.3258 0.9026
0.6604 11.0 8778 0.3179 0.9042
0.6483 12.0 9576 0.3203 0.9059
0.6578 13.0 10374 0.3160 0.9089
0.654 14.0 11172 0.3139 0.9091
0.6418 15.0 11970 0.3091 0.9125
0.6394 16.0 12768 0.3223 0.9029
0.637 17.0 13566 0.3085 0.9153
0.6258 18.0 14364 0.3182 0.9069
0.6438 19.0 15162 0.3127 0.9078
0.6569 20.0 15960 0.3101 0.9114

Framework versions

  • Transformers 4.23.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1