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--- |
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license: apache-2.0 |
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base_model: dima806/music_genres_classification |
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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: music_genres_classification-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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# music_genres_classification-finetuned-gtzan |
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This model is a fine-tuned version of [dima806/music_genres_classification](https://huggingface.co/dima806/music_genres_classification) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5964 |
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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: 5e-05 |
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- train_batch_size: 5 |
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- eval_batch_size: 5 |
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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: 0.12 |
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- num_epochs: 12 |
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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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| 1.8263 | 1.0 | 180 | 1.8672 | 0.53 | |
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| 1.5124 | 2.0 | 360 | 1.7102 | 0.45 | |
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| 1.0715 | 3.0 | 540 | 1.1957 | 0.69 | |
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| 1.0454 | 4.0 | 720 | 1.5712 | 0.68 | |
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| 0.3365 | 5.0 | 900 | 0.9891 | 0.81 | |
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| 0.3502 | 6.0 | 1080 | 1.2261 | 0.74 | |
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| 1.2326 | 7.0 | 1260 | 1.1571 | 0.77 | |
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| 0.5868 | 8.0 | 1440 | 0.7691 | 0.87 | |
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| 0.2718 | 9.0 | 1620 | 0.6720 | 0.88 | |
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| 0.1625 | 10.0 | 1800 | 0.3927 | 0.93 | |
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| 0.2519 | 11.0 | 1980 | 0.5140 | 0.91 | |
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| 0.0701 | 12.0 | 2160 | 0.5964 | 0.88 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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