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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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base_model: facebook/hubert-large-ls960-ft |
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model-index: |
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- name: hubert-large-ls960-ft-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-ls960-ft-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7096 |
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- Accuracy: 0.85 |
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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: 8 |
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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: 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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| 2.2623 | 1.0 | 56 | 2.2399 | 0.21 | |
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| 1.881 | 1.99 | 112 | 1.7105 | 0.41 | |
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| 1.5793 | 2.99 | 168 | 1.6203 | 0.46 | |
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| 1.3018 | 4.0 | 225 | 1.3824 | 0.52 | |
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| 1.0219 | 5.0 | 281 | 0.9899 | 0.66 | |
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| 0.9047 | 5.99 | 337 | 0.8812 | 0.74 | |
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| 0.8353 | 6.99 | 393 | 0.7629 | 0.78 | |
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| 0.659 | 8.0 | 450 | 0.9674 | 0.71 | |
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| 0.645 | 9.0 | 506 | 0.8953 | 0.74 | |
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| 0.6233 | 9.99 | 562 | 0.6638 | 0.8 | |
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| 0.4155 | 10.99 | 618 | 0.6323 | 0.81 | |
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| 0.2689 | 12.0 | 675 | 0.5423 | 0.83 | |
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| 0.3714 | 13.0 | 731 | 0.6770 | 0.83 | |
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| 0.0692 | 13.99 | 787 | 0.6260 | 0.83 | |
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| 0.0778 | 14.99 | 843 | 0.5801 | 0.85 | |
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| 0.187 | 16.0 | 900 | 0.6722 | 0.83 | |
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| 0.1469 | 17.0 | 956 | 0.7473 | 0.85 | |
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| 0.1052 | 17.92 | 1008 | 0.7096 | 0.85 | |
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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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