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nomad-ai
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distilhubert-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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README.md ADDED
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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: 0.87
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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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+ # 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: 0.9031
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: 20
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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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+ | 2.1931 | 1.0 | 113 | 2.0840 | 0.39 |
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+ | 1.5734 | 2.0 | 226 | 1.4764 | 0.53 |
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+ | 1.2619 | 3.0 | 339 | 1.1045 | 0.68 |
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+ | 1.0427 | 4.0 | 452 | 1.0008 | 0.74 |
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+ | 0.7065 | 5.0 | 565 | 0.7131 | 0.83 |
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+ | 0.4206 | 6.0 | 678 | 0.6687 | 0.8 |
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+ | 0.5466 | 7.0 | 791 | 0.5807 | 0.83 |
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+ | 0.1232 | 8.0 | 904 | 0.6143 | 0.83 |
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+ | 0.2593 | 9.0 | 1017 | 0.6080 | 0.89 |
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+ | 0.0496 | 10.0 | 1130 | 0.7360 | 0.84 |
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+ | 0.0127 | 11.0 | 1243 | 0.7648 | 0.85 |
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+ | 0.0993 | 12.0 | 1356 | 0.8416 | 0.85 |
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+ | 0.0068 | 13.0 | 1469 | 0.7966 | 0.85 |
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+ | 0.0054 | 14.0 | 1582 | 0.8122 | 0.86 |
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+ | 0.0044 | 15.0 | 1695 | 0.8788 | 0.87 |
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+ | 0.0037 | 16.0 | 1808 | 0.8760 | 0.87 |
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+ | 0.0892 | 17.0 | 1921 | 0.8911 | 0.87 |
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+ | 0.0032 | 18.0 | 2034 | 0.9083 | 0.86 |
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+ | 0.0029 | 19.0 | 2147 | 0.9172 | 0.86 |
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+ | 0.0037 | 20.0 | 2260 | 0.9031 | 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+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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