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adavirro/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from adavirro. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
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: 0.8249 - Accuracy: 0.87
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From the Hugging Face model README
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:
The initial model trained for 20 epochs and overfit, so I recovered the best epoch (10) and pushed to hub. The metrics above reflect the latest model from epoch 10/checkpoint 2250.
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9486 | 1.0 | 225 | 1.8744 | 0.54 |
| 1.0616 | 2.0 | 450 | 1.2196 | 0.66 |
| 1.0193 | 3.0 | 675 | 0.7841 | 0.78 |
| 0.81 | 4.0 | 900 | 0.7212 | 0.8 |
| 0.2171 | 5.0 | 1125 | 0.7194 | 0.77 |
| 0.0458 | 6.0 | 1350 | 0.8966 | 0.81 |
| 0.3485 | 7.0 | 1575 | 0.7960 | 0.81 |
| 0.09 | 8.0 | 1800 | 1.0860 | 0.82 |
| 0.0031 | 9.0 | 2025 | 0.7744 | 0.84 |
| 0.0026 | 10.0 | 2250 | 0.8249 | 0.87 |