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README.md
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tags:
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- generated_from_trainer
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datasets:
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- gtzan
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metrics:
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- accuracy
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model-index:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilhubert-finetuned-gtzan
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This model
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Accuracy | Validation Loss |
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tags:
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.88
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilhubert-finetuned-gtzan
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This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.76
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- Accuracy: 0.88
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## Model description
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 15
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- .train_test_split(seed=2024, shuffle=True, test_size=0.1)
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### Training results
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| Training Loss | Epoch | Step | Accuracy | Validation Loss |
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