music_genres_classification-finetuned-gtzan
This model is a fine-tuned version of dima806/music_genres_classification on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.4918
- Accuracy: 0.91
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.6393 | 1.0 | 113 | 1.5689 | 0.52 |
1.3821 | 2.0 | 226 | 0.8769 | 0.77 |
0.7728 | 3.0 | 339 | 0.8087 | 0.74 |
0.5591 | 4.0 | 452 | 0.6158 | 0.83 |
0.5464 | 5.0 | 565 | 0.9885 | 0.74 |
0.5483 | 6.0 | 678 | 1.0495 | 0.79 |
0.384 | 7.0 | 791 | 0.5389 | 0.9 |
0.1532 | 8.0 | 904 | 0.4327 | 0.92 |
0.4055 | 9.0 | 1017 | 0.5448 | 0.89 |
0.0351 | 10.0 | 1130 | 0.4918 | 0.91 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
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Model tree for arevin42/music_genres_classification-finetuned-gtzan
Base model
facebook/wav2vec2-base-960h
Finetuned
dima806/music_genres_classification