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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: distilhubert-finetuned-gtzan-v2
    results: []

distilhubert-finetuned-gtzan-v2

This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4959
  • Accuracy: 0.87

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: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7507 1.0 113 1.8033 0.42
1.2592 2.0 226 1.1710 0.71
1.039 3.0 339 0.9022 0.73
0.6122 4.0 452 0.6954 0.82
0.4654 5.0 565 0.6944 0.84
0.2895 6.0 678 0.5393 0.85
0.2114 7.0 791 0.5197 0.86
0.1997 8.0 904 0.5195 0.85
0.1282 9.0 1017 0.4883 0.87
0.3031 10.0 1130 0.4959 0.87

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3