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--- |
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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: 0.85 |
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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: 0.5569 |
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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: 6 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 192 |
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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: 60 |
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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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| No log | 0.85 | 4 | 2.2836 | 0.14 | |
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| 2.2984 | 1.92 | 9 | 2.2574 | 0.18 | |
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| 2.2856 | 2.99 | 14 | 2.2060 | 0.32 | |
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| 2.2478 | 3.84 | 18 | 2.1331 | 0.37 | |
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| 2.1775 | 4.91 | 23 | 1.9859 | 0.47 | |
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| 2.0557 | 5.97 | 28 | 1.8086 | 0.52 | |
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| 1.8764 | 6.83 | 32 | 1.6783 | 0.53 | |
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| 1.7133 | 7.89 | 37 | 1.5235 | 0.54 | |
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| 1.5661 | 8.96 | 42 | 1.4048 | 0.58 | |
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| 1.4544 | 9.81 | 46 | 1.3279 | 0.6 | |
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| 1.3365 | 10.88 | 51 | 1.2591 | 0.67 | |
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| 1.2228 | 11.95 | 56 | 1.1587 | 0.7 | |
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| 1.1298 | 12.8 | 60 | 1.1476 | 0.68 | |
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| 1.0601 | 13.87 | 65 | 1.0066 | 0.77 | |
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| 0.9886 | 14.93 | 70 | 0.9855 | 0.76 | |
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| 0.923 | 16.0 | 75 | 0.9767 | 0.73 | |
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| 0.923 | 16.85 | 79 | 0.8896 | 0.79 | |
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| 0.8539 | 17.92 | 84 | 0.8421 | 0.78 | |
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| 0.788 | 18.99 | 89 | 0.8270 | 0.8 | |
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| 0.7253 | 19.84 | 93 | 0.7764 | 0.82 | |
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| 0.6523 | 20.91 | 98 | 0.6998 | 0.85 | |
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| 0.5853 | 21.97 | 103 | 0.6891 | 0.87 | |
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| 0.5372 | 22.83 | 107 | 0.7106 | 0.8 | |
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| 0.4815 | 23.89 | 112 | 0.6542 | 0.82 | |
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| 0.4461 | 24.96 | 117 | 0.6136 | 0.87 | |
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| 0.3841 | 25.81 | 121 | 0.6338 | 0.81 | |
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| 0.3505 | 26.88 | 126 | 0.6082 | 0.87 | |
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| 0.3143 | 27.95 | 131 | 0.5776 | 0.88 | |
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| 0.2913 | 28.8 | 135 | 0.5833 | 0.86 | |
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| 0.2519 | 29.87 | 140 | 0.5543 | 0.89 | |
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| 0.2234 | 30.93 | 145 | 0.5606 | 0.84 | |
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| 0.1994 | 32.0 | 150 | 0.5726 | 0.86 | |
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| 0.1994 | 32.85 | 154 | 0.5391 | 0.86 | |
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| 0.1789 | 33.92 | 159 | 0.5908 | 0.83 | |
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| 0.1615 | 34.99 | 164 | 0.5498 | 0.85 | |
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| 0.1444 | 35.84 | 168 | 0.5389 | 0.85 | |
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| 0.1303 | 36.91 | 173 | 0.5829 | 0.84 | |
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| 0.1192 | 37.97 | 178 | 0.5278 | 0.87 | |
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| 0.1074 | 38.83 | 182 | 0.6011 | 0.83 | |
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| 0.1001 | 39.89 | 187 | 0.5260 | 0.87 | |
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| 0.0935 | 40.96 | 192 | 0.5778 | 0.84 | |
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| 0.0885 | 41.81 | 196 | 0.5563 | 0.86 | |
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| 0.0827 | 42.88 | 201 | 0.5556 | 0.86 | |
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| 0.0785 | 43.95 | 206 | 0.5807 | 0.84 | |
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| 0.0767 | 44.8 | 210 | 0.5649 | 0.85 | |
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| 0.0722 | 45.87 | 215 | 0.5551 | 0.85 | |
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| 0.0718 | 46.93 | 220 | 0.5432 | 0.86 | |
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| 0.0701 | 48.0 | 225 | 0.5720 | 0.85 | |
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| 0.0701 | 48.85 | 229 | 0.5695 | 0.85 | |
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| 0.068 | 49.92 | 234 | 0.5642 | 0.85 | |
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| 0.0673 | 50.99 | 239 | 0.5571 | 0.85 | |
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| 0.0672 | 51.2 | 240 | 0.5569 | 0.85 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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