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---
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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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- name: distilhubert_finetuned-finetuned-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-finetuned-gtzan
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This model is a fine-tuned version of [JanLilan/distilhubert_finetuned-distilhubert](https://huggingface.co/JanLilan/distilhubert_finetuned-distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6325
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- Accuracy: 0.9
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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: 0.0005
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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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- gradient_accumulation_steps: 2
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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: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.8777 | 0.99 | 33 | 0.4485 | 0.8333 |
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| 0.6913 | 2.0 | 67 | 1.0592 | 0.7 |
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| 0.5494 | 2.99 | 100 | 0.6168 | 0.7667 |
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| 0.3589 | 4.0 | 134 | 0.7820 | 0.7833 |
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| 0.2049 | 4.99 | 167 | 0.9303 | 0.7833 |
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| 0.1663 | 6.0 | 201 | 0.3570 | 0.9 |
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| 0.0446 | 6.99 | 234 | 0.5636 | 0.8667 |
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| 0.0313 | 8.0 | 268 | 0.6592 | 0.85 |
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| 0.0007 | 8.99 | 301 | 0.4721 | 0.8833 |
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| 0.0004 | 9.85 | 330 | 0.6325 | 0.9 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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