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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-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-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: 0.3171 |
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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: 16 |
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- total_train_batch_size: 16 |
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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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- 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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| 1.817 | 1.0 | 56 | 1.5314 | 0.83 | |
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| 1.3804 | 1.99 | 112 | 1.2976 | 0.73 | |
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| 1.1139 | 2.99 | 168 | 0.7886 | 0.9 | |
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| 0.8946 | 3.99 | 224 | 0.6678 | 0.89 | |
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| 0.7045 | 4.98 | 280 | 0.8158 | 0.82 | |
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| 0.7178 | 6.0 | 337 | 0.7588 | 0.83 | |
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| 0.6513 | 6.99 | 393 | 0.4012 | 0.93 | |
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| 0.548 | 7.99 | 449 | 0.3258 | 0.93 | |
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| 0.3329 | 8.99 | 505 | 0.3477 | 0.93 | |
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| 0.2874 | 9.97 | 560 | 0.3171 | 0.94 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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