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distilhubert-finetuned-gtzan – AI Model by ahmadtalha | AlphaNeural AI
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distilhubert-finetuned-gtzan
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transformers
tensorboard
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: 1.0690
eval_accuracy: 0.7327
eval_runtime: 476.8426
eval_samples_per_second: 2.095
eval_steps_per_second: 0.262
epoch: 2.0
step: 250
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 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
