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distilhubert-finetuned-gtzan

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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: ntu-spml/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: 0.87
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+ ---
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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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+
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+ # ntu-spml/distilhubert-finetuned-gtzan
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+
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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: 0.7428
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+ - Accuracy: 0.87
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3.992986714871485e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9807885777224674,0.996064720140604) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 509
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 57 | 2.2832 | 0.3 |
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+ | No log | 2.0 | 114 | 2.2273 | 0.28 |
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+ | No log | 3.0 | 171 | 2.0861 | 0.46 |
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+ | No log | 4.0 | 228 | 1.8473 | 0.5 |
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+ | No log | 5.0 | 285 | 1.5146 | 0.6 |
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+ | No log | 6.0 | 342 | 1.2140 | 0.69 |
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+ | No log | 7.0 | 399 | 0.9856 | 0.74 |
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+ | No log | 8.0 | 456 | 0.8056 | 0.79 |
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+ | 1.6591 | 9.0 | 513 | 0.7135 | 0.8 |
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+ | 1.6591 | 10.0 | 570 | 0.7642 | 0.75 |
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+ | 1.6591 | 11.0 | 627 | 0.6344 | 0.79 |
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+ | 1.6591 | 12.0 | 684 | 0.5982 | 0.83 |
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+ | 1.6591 | 13.0 | 741 | 0.5369 | 0.86 |
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+ | 1.6591 | 14.0 | 798 | 0.7501 | 0.79 |
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+ | 1.6591 | 15.0 | 855 | 0.7493 | 0.78 |
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+ | 1.6591 | 16.0 | 912 | 0.6891 | 0.83 |
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+ | 1.6591 | 17.0 | 969 | 0.7492 | 0.8 |
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+ | 0.2402 | 18.0 | 1026 | 0.6663 | 0.88 |
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+ | 0.2402 | 19.0 | 1083 | 0.5750 | 0.89 |
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+ | 0.2402 | 20.0 | 1140 | 0.8215 | 0.81 |
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+ | 0.2402 | 21.0 | 1197 | 0.7435 | 0.79 |
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+ | 0.2402 | 22.0 | 1254 | 0.8305 | 0.86 |
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+ | 0.2402 | 23.0 | 1311 | 0.7636 | 0.83 |
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+ | 0.2402 | 24.0 | 1368 | 0.9786 | 0.77 |
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+ | 0.2402 | 25.0 | 1425 | 0.7082 | 0.88 |
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+ | 0.2402 | 26.0 | 1482 | 0.7698 | 0.85 |
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+ | 0.0206 | 27.0 | 1539 | 0.7360 | 0.87 |
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+ | 0.0206 | 28.0 | 1596 | 0.8575 | 0.84 |
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+ | 0.0206 | 29.0 | 1653 | 0.7428 | 0.87 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0.dev0
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+ - Pytorch 2.0.1
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+ - Datasets 2.13.2.dev1
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+ - Tokenizers 0.13.3