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distilhubert-finetuned-gtzan – AI Model by farjadmalik | AlphaNeural AI
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distilhubert-finetuned-gtzan
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transformers
safetensors
hubert
audio-classification
generated_from_trainer
marsyas/gtzan
ntu-spml/distilhubert
finetune
apache-2.0
endpoints_compatible
us
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distilhubert-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:
eval_loss: 0.6896
eval_accuracy: 0.81
eval_runtime: 188.3119
eval_samples_per_second: 0.531
eval_steps_per_second: 0.069
epoch: 5.0
step: 565
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
Framework versions
Transformers 4.55.4
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
