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--- |
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base_model: yus988/pingpong-music_genres_classification-finetuned |
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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: pingpong-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: 0.94 |
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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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# pingpong-music_genres_classification-finetuned-gtzan |
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This model is a fine-tuned version of [yus988/pingpong-music_genres_classification-finetuned](https://huggingface.co/yus988/pingpong-music_genres_classification-finetuned) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2967 |
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- Accuracy: 0.94 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 7 |
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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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| 1.4316 | 1.0 | 112 | 1.2668 | 0.75 | |
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| 1.7743 | 1.99 | 224 | 1.0659 | 0.64 | |
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| 0.9712 | 3.0 | 337 | 0.5958 | 0.84 | |
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| 1.2043 | 4.0 | 449 | 0.6563 | 0.86 | |
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| 0.5506 | 4.99 | 561 | 0.3875 | 0.9 | |
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| 0.5882 | 6.0 | 674 | 0.4775 | 0.9 | |
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| 0.3522 | 6.98 | 784 | 0.2967 | 0.94 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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