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metadata
tags:
  - generated_from_trainer
datasets:
  - superb
metrics:
  - accuracy
model-index:
  - name: trillsson3-ft-keyword-spotting-11
    results: []

trillsson3-ft-keyword-spotting-11

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: 0.3166
  • 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