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ntu-spml-distilhubert-base-finetuned-gtzan – AI Model by Janos98 | AlphaNeural AI
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Janos98
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ntu-spml-distilhubert-base-finetuned-gtzan
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transformers
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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ntu-spml/distilhubert-base-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: 1.6070
Accuracy: 0.44
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: 0.001
train_batch_size: 2
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 15
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
12.3613
1.0
57
1.5334
0.45
15.9173
2.0
114
1.8506
0.28
15.0443
3.0
171
1.7801
0.39
12.3451
4.0
228
1.6070
0.44
Framework versions
Transformers 5.13.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
