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metoonhathung/music-generation

sourceHugging Facemitupdated 1y agoView on Hugging Face
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Model Card

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music-generation

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.5312

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: 0.0001
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 256
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 100
  • —num_epochs: 20
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
3.72380.92171002.8460
2.46431.83872001.8829
1.83392.75583001.4234
1.50133.67284001.2203
1.31254.58995001.0966
1.18995.50696001.0028
1.09826.42407000.9353
1.03027.34108000.8779
0.97668.25819000.8276
0.92439.175110000.7757
0.882510.092211000.7345
0.84511.009212000.7000
0.808311.930913000.6624
0.778412.847914000.6328
0.750213.765015000.6052
0.728114.682016000.5816
0.707215.599117000.5622
0.690316.516118000.5486
0.679617.433219000.5386
0.670518.350220000.5335
0.664619.267321000.5312

Framework versions

  • —Transformers 4.55.0
  • —Pytorch 2.6.0+cu124
  • —Datasets 4.0.0
  • —Tokenizers 0.21.4