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distilhubert-finetuned-gtzan – AI Model by Isaacgv | AlphaNeural AI
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Isaacgv
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distilhubert-finetuned-gtzan
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transformers
pytorch
tensorboard
hubert
audio-classification
generated_from_trainer
marsyas/gtzan
ntu-spml/distilhubert
finetune
apache-2.0
model-index
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:
Loss: 0.5655
Accuracy: 0.88
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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3836
0.98
14
0.5798
0.82
0.3357
1.96
28
0.5655
0.88
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.0
Tokenizers 0.13.3
