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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: HamzaSidhu786/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: 0.88 |
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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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# HamzaSidhu786/distilhubert-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6028 |
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- Accuracy: 0.88 |
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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: 3e-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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- 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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| 2.0751 | 1.0 | 113 | 2.0343 | 0.6 | |
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| 1.5734 | 2.0 | 226 | 1.6338 | 0.58 | |
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| 1.3801 | 3.0 | 339 | 1.2674 | 0.7 | |
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| 1.0384 | 4.0 | 452 | 1.1376 | 0.68 | |
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| 0.973 | 5.0 | 565 | 0.9849 | 0.73 | |
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| 1.0033 | 6.0 | 678 | 0.7686 | 0.76 | |
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| 0.6347 | 7.0 | 791 | 0.5909 | 0.87 | |
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| 0.6537 | 8.0 | 904 | 0.9489 | 0.75 | |
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| 0.359 | 9.0 | 1017 | 0.7478 | 0.81 | |
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| 0.2268 | 10.0 | 1130 | 0.6247 | 0.84 | |
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| 0.2674 | 11.0 | 1243 | 0.6437 | 0.84 | |
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| 0.2237 | 12.0 | 1356 | 0.7997 | 0.81 | |
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| 0.1418 | 13.0 | 1469 | 0.7738 | 0.84 | |
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| 0.1201 | 14.0 | 1582 | 0.5696 | 0.87 | |
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| 0.019 | 15.0 | 1695 | 0.8173 | 0.84 | |
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| 0.0175 | 16.0 | 1808 | 0.6395 | 0.88 | |
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| 0.16 | 17.0 | 1921 | 0.6062 | 0.87 | |
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| 0.0137 | 18.0 | 2034 | 0.5422 | 0.9 | |
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| 0.0127 | 19.0 | 2147 | 0.6421 | 0.88 | |
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| 0.0129 | 20.0 | 2260 | 0.6028 | 0.88 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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