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distilhubert-finetuned-gtzan – AI Model by AdonaiHS | AlphaNeural AI
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AdonaiHS
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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: 0.9423
Accuracy: 0.77
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-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 3000
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.1574
8.85
500
1.8008
0.66
1.5882
17.7
1000
1.3509
0.7
1.2416
26.55
1500
1.1347
0.72
1.037
35.4
2000
1.0163
0.74
0.9152
44.25
2500
0.9583
0.76
0.8556
53.1
3000
0.9423
0.77
Framework versions
Transformers 4.32.0
Pytorch 1.12.1+cu113
Datasets 2.14.4
Tokenizers 0.13.3
