Derek Thomas
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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-base-ls960-finetuned-gtzan-efficient
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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-base-ls960-finetuned-gtzan-efficient
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0959
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- Accuracy: 0.89
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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: 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: 30
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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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| 2.1988 | 1.0 | 113 | 2.1353 | 0.36 |
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| 1.6317 | 2.0 | 226 | 1.7387 | 0.39 |
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| 1.4411 | 3.0 | 339 | 1.3925 | 0.46 |
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| 0.8491 | 4.0 | 452 | 1.0834 | 0.65 |
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| 2.1748 | 5.0 | 565 | 1.1530 | 0.64 |
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| 1.4915 | 6.0 | 678 | 0.9865 | 0.69 |
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| 0.4322 | 7.0 | 791 | 1.3910 | 0.6 |
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| 0.6867 | 8.0 | 904 | 1.1252 | 0.7 |
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| 0.0758 | 9.0 | 1017 | 0.7395 | 0.75 |
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| 1.8782 | 10.0 | 1130 | 0.9792 | 0.77 |
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| 1.0492 | 11.0 | 1243 | 0.8810 | 0.75 |
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| 0.0376 | 12.0 | 1356 | 0.7031 | 0.81 |
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| 0.0648 | 13.0 | 1469 | 0.7527 | 0.82 |
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| 1.1951 | 14.0 | 1582 | 0.7731 | 0.84 |
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| 0.0071 | 15.0 | 1695 | 0.9237 | 0.83 |
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| 0.0095 | 16.0 | 1808 | 0.8471 | 0.85 |
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| 0.0014 | 17.0 | 1921 | 1.0585 | 0.87 |
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| 0.0007 | 18.0 | 2034 | 1.0959 | 0.89 |
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| 0.0003 | 19.0 | 2147 | 1.3957 | 0.86 |
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| 3.0069 | 20.0 | 2260 | 1.6382 | 0.84 |
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| 0.0 | 21.0 | 2373 | 1.3385 | 0.88 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.1.0.dev20230627+cu121
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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