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ai_music_detection_large_60s – AI Model by AI-Music-Detection | AlphaNeural AI
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AI-Music-Detection
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ai_music_detection_large_60s
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transformers
tensorboard
safetensors
audio-spectrogram-transformer
audio-classification
generated_from_trainer
SleepyJesse/ai_music_large
MIT/ast-finetuned-audioset-10-10-0.4593
finetune
endpoints_compatible
us
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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
