End of training
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- model.safetensors +1 -1
README.md
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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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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---
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/soundofai/huggingface-audio-course/runs/
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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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## Model description
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 20
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### Framework versions
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- Transformers 4.41.0.dev0
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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: 0.92
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/soundofai/huggingface-audio-course/runs/nfwkhlry)
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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: 0.3597
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- Accuracy: 0.92
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## Model description
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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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| 0.5671 | 0.9956 | 112 | 0.5463 | 0.85 |
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| 0.7083 | 2.0 | 225 | 0.6822 | 0.78 |
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| 0.2257 | 2.9956 | 337 | 0.5415 | 0.85 |
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| 0.028 | 4.0 | 450 | 0.5070 | 0.9 |
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| 0.0526 | 4.9956 | 562 | 0.8882 | 0.82 |
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| 0.0628 | 6.0 | 675 | 0.9979 | 0.79 |
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| 0.0025 | 6.9956 | 787 | 0.5942 | 0.88 |
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| 0.0005 | 8.0 | 900 | 0.6327 | 0.9 |
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| 0.0005 | 8.9956 | 1012 | 0.4033 | 0.9 |
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| 0.0009 | 10.0 | 1125 | 0.4190 | 0.88 |
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| 0.0001 | 10.9956 | 1237 | 0.3672 | 0.93 |
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| 0.0001 | 12.0 | 1350 | 0.3615 | 0.91 |
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| 0.0001 | 12.9956 | 1462 | 0.3631 | 0.92 |
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| 0.0001 | 14.0 | 1575 | 0.3597 | 0.92 |
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| 0.0001 | 14.9956 | 1687 | 0.3604 | 0.92 |
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| 0.0 | 16.0 | 1800 | 0.3589 | 0.92 |
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| 0.0 | 16.9956 | 1912 | 0.3597 | 0.92 |
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| 0.0434 | 18.0 | 2025 | 0.3590 | 0.92 |
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| 0.0 | 18.9956 | 2137 | 0.3594 | 0.92 |
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| 0.0 | 19.9111 | 2240 | 0.3597 | 0.92 |
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### Framework versions
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- Transformers 4.41.0.dev0
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model.safetensors
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