kurianbenoy/hfa-distilhubert-finetuned-gtzan-exercise

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distilhubert-finetuned-gtzan

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: 0.8097
• —Accuracy: 0.79

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: 0.001
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 5
• —totaltrainbatch_size: 40
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.30.2
• —Pytorch 2.0.1
• —Datasets 2.13.1
• —Tokenizers 0.13.3