End of training
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README.md
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---
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license:
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base_model:
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tags:
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- generated_from_trainer
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datasets:
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# distilhubert-finetuned-gtzan
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- eval_loss: 0.8117
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- eval_accuracy: 0.83
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- eval_runtime: 46.4112
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- eval_samples_per_second: 2.155
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- eval_steps_per_second: 0.539
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- epoch: 12.9956
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- step: 731
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs:
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.19.1
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---
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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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# distilhubert-finetuned-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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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.1.2
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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