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--- |
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license: bsd-3-clause |
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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: ast-finetuned-audioset-10-10-0.4593-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: 0.9 |
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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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# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan |
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This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4717 |
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- Accuracy: 0.9 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 20 |
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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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| 0.7581 | 1.0 | 56 | 0.7029 | 0.78 | |
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| 0.3942 | 1.99 | 112 | 0.4646 | 0.86 | |
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| 0.3298 | 2.99 | 168 | 0.3861 | 0.88 | |
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| 0.1227 | 4.0 | 225 | 0.4702 | 0.86 | |
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| 0.0774 | 5.0 | 281 | 0.4492 | 0.9 | |
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| 0.0039 | 5.99 | 337 | 0.4607 | 0.9 | |
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| 0.0014 | 6.99 | 393 | 0.5022 | 0.9 | |
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| 0.0022 | 8.0 | 450 | 0.4711 | 0.9 | |
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| 0.0193 | 9.0 | 506 | 0.5226 | 0.86 | |
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| 0.0004 | 9.99 | 562 | 0.6055 | 0.82 | |
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| 0.0003 | 10.99 | 618 | 0.4793 | 0.89 | |
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| 0.0002 | 12.0 | 675 | 0.5052 | 0.9 | |
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| 0.0002 | 13.0 | 731 | 0.4652 | 0.89 | |
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| 0.0001 | 13.99 | 787 | 0.4617 | 0.9 | |
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| 0.0001 | 14.99 | 843 | 0.4653 | 0.9 | |
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| 0.0001 | 16.0 | 900 | 0.4635 | 0.91 | |
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| 0.0001 | 17.0 | 956 | 0.4693 | 0.9 | |
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| 0.0001 | 17.99 | 1012 | 0.4697 | 0.9 | |
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| 0.0001 | 18.99 | 1068 | 0.4715 | 0.9 | |
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| 0.0025 | 19.91 | 1120 | 0.4717 | 0.9 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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