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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: 0.6477 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 12 |
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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: 15 |
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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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| 2.1618 | 1.0 | 75 | 2.0497 | 0.36 | |
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| 1.5327 | 2.0 | 150 | 1.4568 | 0.62 | |
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| 1.1622 | 3.0 | 225 | 1.1626 | 0.66 | |
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| 0.849 | 4.0 | 300 | 0.9894 | 0.74 | |
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| 0.6072 | 5.0 | 375 | 0.8128 | 0.75 | |
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| 0.4014 | 6.0 | 450 | 0.7118 | 0.79 | |
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| 0.3285 | 7.0 | 525 | 0.7482 | 0.83 | |
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| 0.3074 | 8.0 | 600 | 0.5633 | 0.85 | |
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| 0.242 | 9.0 | 675 | 0.6613 | 0.82 | |
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| 0.069 | 10.0 | 750 | 0.5173 | 0.85 | |
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| 0.1281 | 11.0 | 825 | 0.6102 | 0.83 | |
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| 0.0334 | 12.0 | 900 | 0.5990 | 0.84 | |
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| 0.0307 | 13.0 | 975 | 0.6227 | 0.86 | |
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| 0.0339 | 14.0 | 1050 | 0.6331 | 0.85 | |
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| 0.0239 | 15.0 | 1125 | 0.6477 | 0.85 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
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