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distilhubert-finetuned-gtzan – AI Model by wronaq | AlphaNeural AI
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wronaq
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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
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: 0.9719
Accuracy: 0.87
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.002
1.0
113
0.7959
0.88
0.0009
2.0
226
1.0211
0.86
0.1645
3.0
339
0.9719
0.87
Framework versions
Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
