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distilhubert-finetuned-gtzan – AI Model by KoRiF | AlphaNeural AI
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KoRiF
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distilhubert-finetuned-gtzan
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transformers
pytorch
tensorboard
safetensors
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: 0.7321
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: 2e-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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.0326
1.0
7
0.5762
0.9
0.95
2.0
14
0.5924
0.9
0.9304
3.0
21
0.5446
0.9
0.4207
4.0
28
0.6466
0.88
0.261
5.0
35
0.7321
0.88
Framework versions
Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
