cleandata/distilhubert-finetuned-gtzan_accuracy_93

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distilhubert-finetuned-gtzanaccuracy93

This model is a fine-tuned version of yuval6967/distilhubert-finetuned-gtzan on the GTZAN dataset.

It achieves the following results on the evaluation set:

• —Loss: 0.5121
• —_Accuracy: 0.93_

Model description

• —Fine-tuned model to demonstrate > 87% accuracy for the Huggingface Audio course

Intended uses & limitations

• —Model is built to identify the genre of music based on a ~30 sec clip

Training and evaluation data

More information needed

Training procedure

• —test_size = 0.20 was used for the split

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 5e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.30.2
• —Pytorch 2.0.1+cu118
• —Datasets 2.13.1
• —Tokenizers 0.13.3