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update model card README.md
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README.md
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---
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license: apache-2.0
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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: hubert-large-ll60k-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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# hubert-large-ll60k-finetuned-gtzan
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This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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- Accuracy: 0.1
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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: 8e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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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: 18
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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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| 2.2369 | 1.0 | 112 | 2.1698 | 0.32 |
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| 1.9093 | 2.0 | 225 | 1.7851 | 0.34 |
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| 1.5339 | 3.0 | 337 | 1.4068 | 0.46 |
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| 1.4127 | 4.0 | 450 | 1.2916 | 0.53 |
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| 0.991 | 5.0 | 562 | 1.0534 | 0.58 |
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| 0.8365 | 6.0 | 675 | 0.9250 | 0.67 |
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| 0.6994 | 7.0 | 787 | 1.0032 | 0.72 |
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| 1.3372 | 8.0 | 900 | nan | 0.41 |
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| 4.3377 | 9.0 | 1012 | nan | 0.29 |
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| 0.0 | 10.0 | 1125 | nan | 0.1 |
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| 0.0 | 11.0 | 1237 | nan | 0.1 |
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| 0.0 | 12.0 | 1350 | nan | 0.1 |
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| 0.0 | 13.0 | 1462 | nan | 0.1 |
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| 0.0 | 14.0 | 1575 | nan | 0.1 |
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| 0.0 | 15.0 | 1687 | nan | 0.1 |
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| 0.0 | 16.0 | 1800 | nan | 0.1 |
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| 0.0 | 17.0 | 1912 | nan | 0.1 |
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| 0.0 | 17.92 | 2016 | nan | 0.1 |
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### Framework versions
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- Transformers 4.30.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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