ai_music_detection_large_60s
This model was trained from mit/ast-finetuned-audioset-10-10-0.4593 on the SleepyJesse/ai_music_large dataset.
Please see the code in the Jupyter Notebook in files.
Model description
The model was trained with max_length = 6000, which is 60 seconds.
Intended uses & limitations
This model is used to classify a given music piece is AI-generated or human-composed.
Training and evaluation data
The SleepyJesse/ai_music_large dataset was used, with 80% train/test split, and 0.8 probability for audio data augmentation.
Training procedure
See ai_music_detection_new_large_60.ipynb and training metrics.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 16
- 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
- num_epochs: 10
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for SleepyJesse/ai_music_detection_large_60s
Base model
MIT/ast-finetuned-audioset-10-10-0.4593