readme: ---
  tags:
  - audio-classification
  - generated_from_trainer
  datasets:
  - superb
  metrics:
  - accuracy
  model-index:
  - name: trillsson3-ft-keyword-spotting-11
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # trillsson3-ft-keyword-spotting-11
  
  This model is a fine-tuned version of [vumichien/nonsemantic-speech-trillsson3](https://huggingface.co/vumichien/nonsemantic-speech-trillsson3) on the superb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3166
  - Accuracy: 0.9088
  
  ## 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: 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: 20.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.9219        | 1.0   | 399  | 1.2023          | 0.6217   |
  | 0.9604        | 2.0   | 798  | 0.5437          | 0.8117   |
  | 0.7608        | 3.0   | 1197 | 0.4222          | 0.8888   |
  | 0.7045        | 4.0   | 1596 | 0.3881          | 0.8932   |
  | 0.659         | 5.0   | 1995 | 0.3706          | 0.8847   |
  | 0.6541        | 6.0   | 2394 | 0.3553          | 0.8917   |
  | 0.6448        | 7.0   | 2793 | 0.3482          | 0.8953   |
  | 0.6288        | 8.0   | 3192 | 0.3409          | 0.8989   |
  | 0.641         | 9.0   | 3591 | 0.3297          | 0.9051   |
  | 0.6369        | 10.0  | 3990 | 0.3325          | 0.9042   |
  | 0.6218        | 11.0  | 4389 | 0.3250          | 0.9064   |
  | 0.6247        | 12.0  | 4788 | 0.3312          | 0.8959   |
  | 0.6284        | 13.0  | 5187 | 0.3217          | 0.9069   |
  | 0.6213        | 14.0  | 5586 | 0.3301          | 0.8978   |
  | 0.6274        | 15.0  | 5985 | 0.3180          | 0.9081   |
  | 0.627         | 16.0  | 6384 | 0.3257          | 0.9020   |
  | 0.6227        | 17.0  | 6783 | 0.3193          | 0.9056   |
  | 0.6192        | 18.0  | 7182 | 0.3199          | 0.9066   |
  | 0.6075        | 19.0  | 7581 | 0.3183          | 0.9073   |
  | 0.6196        | 20.0  | 7980 | 0.3166          | 0.9088   |
  
  
  ### Framework versions
  
  - Transformers 4.23.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  