genre-recognizer-finetuned-gtzan_dset-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: 0.4890
- Accuracy: 0.8446
- Precision: 0.8423
- Recall: 0.8446
- F1: 0.8429
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
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.33.1
- Pytorch 1.10.2+cu111
- Datasets 2.14.5
- Tokenizers 0.13.3