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whisper-tiny-speech-commands

This model is a fine-tuned version of openai/whisper-tiny on the speech_commands dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3232
  • Accuracy: 0.8040

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: 5e-05
  • train_batch_size: 96
  • eval_batch_size: 96
  • seed: 42
  • 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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4229 1.0 412 1.1286 0.7936
0.1396 2.0 824 1.0506 0.7995
0.1323 3.0 1236 1.1224 0.7977
0.0528 4.0 1648 1.0810 0.8004
0.0889 5.0 2060 0.9224 0.8022
0.076 6.0 2472 1.0393 0.7981
0.0429 7.0 2884 1.1115 0.7990
0.0007 8.0 3296 1.1706 0.8026
0.0129 9.0 3708 1.0661 0.8013
0.0161 10.0 4120 1.0114 0.7990
0.0205 11.0 4532 1.2129 0.8031
0.0107 12.0 4944 1.1118 0.8026
0.0099 13.0 5356 0.9145 0.8031
0.0002 14.0 5768 1.1582 0.7999
0.0001 15.0 6180 1.2959 0.8035
0.0163 16.0 6592 1.0992 0.8026
0.0001 17.0 7004 1.2913 0.8035
0.0003 18.0 7416 1.3232 0.8040
0.0001 19.0 7828 1.3720 0.8040
0.0001 20.0 8240 1.3889 0.8040

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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