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--- |
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license: apache-2.0 |
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base_model: bookbot/distil-ast-audioset |
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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: distil-ast-audioset-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: 0.89 |
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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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# distil-ast-audioset-finetuned-gtzan |
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This model is a fine-tuned version of [bookbot/distil-ast-audioset](https://huggingface.co/bookbot/distil-ast-audioset) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4548 |
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- Accuracy: 0.89 |
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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: 20 |
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- eval_batch_size: 20 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 80 |
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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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| 1.9887 | 0.9778 | 11 | 0.9550 | 0.79 | |
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| 0.8046 | 1.9556 | 22 | 0.6496 | 0.79 | |
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| 0.517 | 2.9333 | 33 | 0.5969 | 0.8 | |
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| 0.3425 | 4.0 | 45 | 0.4936 | 0.87 | |
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| 0.1616 | 4.9778 | 56 | 0.5090 | 0.88 | |
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| 0.1274 | 5.9556 | 67 | 0.4367 | 0.88 | |
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| 0.071 | 6.9333 | 78 | 0.4128 | 0.88 | |
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| 0.026 | 8.0 | 90 | 0.4548 | 0.89 | |
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| 0.0185 | 8.9778 | 101 | 0.3586 | 0.88 | |
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| 0.0089 | 9.7778 | 110 | 0.3642 | 0.88 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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