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distilhubert-finetuned-gtzan – AI Model by Shijian | AlphaNeural AI
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Shijian
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distilhubert-finetuned-gtzan
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transformers
pytorch
tensorboard
hubert
audio-classification
generated_from_trainer
marsyas/gtzan
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: 0.6312
eval_accuracy: 0.88
eval_runtime: 53.355
eval_samples_per_second: 1.874
eval_steps_per_second: 0.244
epoch: 12.0
step: 1356
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
