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exemple2-finetuned-gtzan – AI Model by rcodina | AlphaNeural AI
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rcodina
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exemple2-finetuned-gtzan
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transformers
tensorboard
safetensors
hubert
audio-classification
generated_from_trainer
gtzan
ntu-spml/distilhubert
finetune
apache-2.0
model-index
endpoints_compatible
us
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exemple2-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: 1.5347
Accuracy: 0.66
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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
0.99
56
1.6601
0.62
No log
1.98
112
1.5347
0.66
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
