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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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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-gtzan
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: GTZAN
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type: marsyas/gtzan
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config: all
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split: train
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args: all
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.84
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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-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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- Loss: 0.5606
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- Accuracy: 0.84
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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: 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: Use 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: 0.1
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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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| 1.971 | 1.0 | 113 | 1.8364 | 0.56 |
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| 1.1506 | 2.0 | 226 | 1.2390 | 0.63 |
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| 1.0134 | 3.0 | 339 | 1.0482 | 0.69 |
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| 0.6013 | 4.0 | 452 | 0.8325 | 0.75 |
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| 0.5541 | 5.0 | 565 | 0.6878 | 0.81 |
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| 0.4044 | 6.0 | 678 | 0.6110 | 0.8 |
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| 0.2903 | 7.0 | 791 | 0.4940 | 0.83 |
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| 0.0975 | 8.0 | 904 | 0.5548 | 0.83 |
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| 0.1276 | 9.0 | 1017 | 0.5400 | 0.84 |
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| 0.0782 | 10.0 | 1130 | 0.5606 | 0.84 |
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### Framework versions
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- Transformers 4.48.2
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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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