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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: hubert-base-ls960-finetuned-gtzan-efficient
    results: []

hubert-base-ls960-finetuned-gtzan-efficient

This model is a fine-tuned version of facebook/hubert-base-ls960 on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0959
  • Accuracy: 0.89

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: 8
  • eval_batch_size: 8
  • 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: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.1988 1.0 113 2.1353 0.36
1.6317 2.0 226 1.7387 0.39
1.4411 3.0 339 1.3925 0.46
0.8491 4.0 452 1.0834 0.65
2.1748 5.0 565 1.1530 0.64
1.4915 6.0 678 0.9865 0.69
0.4322 7.0 791 1.3910 0.6
0.6867 8.0 904 1.1252 0.7
0.0758 9.0 1017 0.7395 0.75
1.8782 10.0 1130 0.9792 0.77
1.0492 11.0 1243 0.8810 0.75
0.0376 12.0 1356 0.7031 0.81
0.0648 13.0 1469 0.7527 0.82
1.1951 14.0 1582 0.7731 0.84
0.0071 15.0 1695 0.9237 0.83
0.0095 16.0 1808 0.8471 0.85
0.0014 17.0 1921 1.0585 0.87
0.0007 18.0 2034 1.0959 0.89
0.0003 19.0 2147 1.3957 0.86
3.0069 20.0 2260 1.6382 0.84
0.0 21.0 2373 1.3385 0.88

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.1.0.dev20230627+cu121
  • Datasets 2.13.1
  • Tokenizers 0.13.3