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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/naganithin2004/huggingface/runs/i8in1y3p) |
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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: 1.7615 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 50 |
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- mixed_precision_training: Native AMP |
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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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| 2.2914 | 1.0 | 57 | 2.2595 | 0.25 | |
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| 2.1225 | 2.0 | 114 | 2.0265 | 0.57 | |
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| 1.7631 | 3.0 | 171 | 1.6482 | 0.59 | |
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| 1.3445 | 4.0 | 228 | 1.3380 | 0.62 | |
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| 1.1548 | 5.0 | 285 | 1.0589 | 0.72 | |
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| 0.9289 | 6.0 | 342 | 0.8541 | 0.76 | |
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| 0.708 | 7.0 | 399 | 0.7628 | 0.79 | |
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| 0.4497 | 8.0 | 456 | 0.7088 | 0.82 | |
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| 0.4061 | 9.0 | 513 | 0.6118 | 0.85 | |
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| 0.286 | 10.0 | 570 | 0.6684 | 0.79 | |
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| 0.1739 | 11.0 | 627 | 0.5965 | 0.83 | |
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| 0.1103 | 12.0 | 684 | 0.8414 | 0.81 | |
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| 0.0922 | 13.0 | 741 | 0.5937 | 0.87 | |
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| 0.0166 | 14.0 | 798 | 0.5786 | 0.86 | |
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| 0.0075 | 15.0 | 855 | 0.7950 | 0.84 | |
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| 0.0014 | 16.0 | 912 | 0.8492 | 0.87 | |
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| 0.0006 | 17.0 | 969 | 1.2642 | 0.82 | |
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| 0.0815 | 18.0 | 1026 | 1.1173 | 0.87 | |
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| 0.0 | 19.0 | 1083 | 1.2181 | 0.86 | |
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| 0.0 | 20.0 | 1140 | 1.6673 | 0.85 | |
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| 0.0 | 21.0 | 1197 | 1.4749 | 0.86 | |
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| 0.0611 | 22.0 | 1254 | 2.2533 | 0.82 | |
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| 0.0978 | 23.0 | 1311 | 2.0092 | 0.86 | |
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| 0.0 | 24.0 | 1368 | 2.3586 | 0.83 | |
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| 0.0 | 25.0 | 1425 | 1.7617 | 0.86 | |
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| 0.0 | 26.0 | 1482 | 1.7425 | 0.86 | |
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| 0.0 | 27.0 | 1539 | 1.8418 | 0.85 | |
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| 0.0 | 28.0 | 1596 | 1.6987 | 0.87 | |
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| 0.0 | 29.0 | 1653 | 1.9399 | 0.85 | |
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| 0.0 | 30.0 | 1710 | 2.4230 | 0.81 | |
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| 0.0 | 31.0 | 1767 | 1.4312 | 0.88 | |
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| 0.1807 | 32.0 | 1824 | 1.5278 | 0.87 | |
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| 0.0 | 33.0 | 1881 | 1.3795 | 0.88 | |
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| 0.0 | 34.0 | 1938 | 1.5051 | 0.88 | |
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| 0.0 | 35.0 | 1995 | 1.6587 | 0.85 | |
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| 0.0 | 36.0 | 2052 | 1.6256 | 0.86 | |
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| 0.0 | 37.0 | 2109 | 1.7290 | 0.85 | |
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| 0.0 | 38.0 | 2166 | 1.8676 | 0.87 | |
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| 0.0 | 39.0 | 2223 | 1.8963 | 0.86 | |
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| 0.166 | 40.0 | 2280 | 1.7057 | 0.85 | |
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| 0.1293 | 41.0 | 2337 | 1.4235 | 0.87 | |
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| 0.1491 | 42.0 | 2394 | 1.7916 | 0.85 | |
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| 0.1416 | 43.0 | 2451 | 1.8634 | 0.85 | |
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| 0.0 | 44.0 | 2508 | 1.6286 | 0.86 | |
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| 0.0526 | 45.0 | 2565 | 1.6242 | 0.86 | |
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| 0.0 | 46.0 | 2622 | 1.7576 | 0.85 | |
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| 0.0 | 47.0 | 2679 | 1.7897 | 0.85 | |
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| 0.0 | 48.0 | 2736 | 1.7571 | 0.85 | |
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| 0.0018 | 49.0 | 2793 | 1.6993 | 0.85 | |
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| 0.0 | 50.0 | 2850 | 1.7615 | 0.85 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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