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distilhubert-finetuned-gtzan – AI Model by grs32 | 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: 0.4572
eval_accuracy: 0.89
eval_runtime: 49.0273
eval_samples_per_second: 2.04
eval_steps_per_second: 0.51
epoch: 7.0
step: 791
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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.2
num_epochs: 10
mixed_precision_training: Native AMP
Framework versions
Transformers 5.0.0.dev0
Pytorch 2.8.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1
