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---
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library_name: transformers
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license: apache-2.0
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base_model: ntu-spml/distilhubert
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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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model-index:
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- name: distilhubert-finetuned-hyperparam-gtzan
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results: []
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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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should probably proofread and complete it, then remove this comment. -->
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# distilhubert-finetuned-hyperparam-gtzan
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.6969
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- eval_model_preparation_time: 0.0031
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- eval_accuracy: 0.86
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- eval_runtime: 69.8954
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- eval_samples_per_second: 1.431
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- eval_steps_per_second: 0.186
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- step: 0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.2
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- num_epochs: 30
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### Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.6.0+cu126
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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