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--- |
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license: apache-2.0 |
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tags: |
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- music |
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- genre |
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- classification |
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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_accuracy_93 |
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results: [] |
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language: |
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- en |
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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_accuracy_93 |
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### This model is a fine-tuned version of [yuval6967/distilhubert-finetuned-gtzan](https://huggingface.co/yuval6967/distilhubert-finetuned-gtzan) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5121 |
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- __Accuracy: 0.93__ |
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## Model description |
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- Fine-tuned model to demonstrate > 87% accuracy for the [Huggingface Audio course](https://huggingface.co/learn/audio-course/chapter0/introduction) |
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## Intended uses & limitations |
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- Model is built to identify the genre of music based on a ~30 sec clip |
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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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- test_size = 0.20 was used for the split |
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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: 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: 10 |
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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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| 0.0316 | 1.0 | 100 | 0.4338 | 0.895 | |
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| 0.0031 | 2.0 | 200 | 0.7039 | 0.86 | |
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| 0.0069 | 3.0 | 300 | 0.4526 | 0.925 | |
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| 0.1799 | 4.0 | 400 | 0.7071 | 0.88 | |
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| 0.1783 | 5.0 | 500 | 0.5923 | 0.92 | |
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| 0.0011 | 6.0 | 600 | 0.5498 | 0.92 | |
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| 0.0005 | 7.0 | 700 | 0.4927 | 0.925 | |
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| 0.0005 | 8.0 | 800 | 0.6172 | 0.915 | |
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| 0.0004 | 9.0 | 900 | 0.4988 | 0.925 | |
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| 0.0004 | 10.0 | 1000 | 0.5121 | 0.93 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
