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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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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 |
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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: 0.88 |
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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 |
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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: 0.6645 |
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- Accuracy: 0.88 |
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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: 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: 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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| 2.2685 | 1.0 | 56 | 2.2069 | 0.44 | |
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| 2.0208 | 1.99 | 112 | 1.8352 | 0.46 | |
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| 1.7603 | 2.99 | 168 | 1.5275 | 0.49 | |
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| 1.4843 | 4.0 | 225 | 1.4296 | 0.52 | |
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| 1.347 | 5.0 | 281 | 1.2222 | 0.52 | |
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| 1.2364 | 5.99 | 337 | 1.1477 | 0.62 | |
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| 1.2082 | 6.99 | 393 | 1.0181 | 0.67 | |
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| 0.9861 | 8.0 | 450 | 0.9598 | 0.71 | |
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| 0.752 | 9.0 | 506 | 0.7499 | 0.77 | |
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| 1.006 | 9.99 | 562 | 0.8190 | 0.79 | |
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| 0.6725 | 10.99 | 618 | 0.8798 | 0.75 | |
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| 0.7457 | 12.0 | 675 | 0.6276 | 0.81 | |
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| 0.4605 | 13.0 | 731 | 0.6086 | 0.85 | |
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| 0.5751 | 13.99 | 787 | 0.6894 | 0.75 | |
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| 0.4886 | 14.99 | 843 | 0.6109 | 0.83 | |
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| 0.2429 | 16.0 | 900 | 0.6076 | 0.85 | |
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| 0.3084 | 17.0 | 956 | 0.4646 | 0.86 | |
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| 0.3762 | 17.99 | 1012 | 0.8349 | 0.81 | |
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| 0.2897 | 18.99 | 1068 | 0.4509 | 0.89 | |
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| 0.1296 | 20.0 | 1125 | 0.6791 | 0.86 | |
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| 0.1291 | 21.0 | 1181 | 0.6466 | 0.85 | |
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| 0.3784 | 21.99 | 1237 | 0.6272 | 0.88 | |
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| 0.1156 | 22.99 | 1293 | 0.7916 | 0.85 | |
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| 0.2093 | 24.0 | 1350 | 0.6536 | 0.85 | |
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| 0.2167 | 25.0 | 1406 | 0.7050 | 0.87 | |
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| 0.1095 | 25.99 | 1462 | 0.6128 | 0.88 | |
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| 0.1004 | 26.99 | 1518 | 0.6092 | 0.89 | |
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| 0.0897 | 28.0 | 1575 | 0.6730 | 0.88 | |
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| 0.083 | 29.0 | 1631 | 0.6396 | 0.89 | |
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| 0.0343 | 29.87 | 1680 | 0.6645 | 0.88 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
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