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README.md
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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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metrics:
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- accuracy
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model-index:
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- name: trainer
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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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# trainer
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3684
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- Accuracy: 0.9275
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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: 0.0001
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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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_steps: 50
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- training_steps: 1000
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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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| 4.2624 | 2.0 | 50 | 0.3928 | 0.88 |
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| 0.9069 | 4.0 | 100 | 0.3259 | 0.9025 |
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| 0.9069 | 6.0 | 150 | 0.2775 | 0.93 |
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| 0.0567 | 8.0 | 200 | 0.3220 | 0.9075 |
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| 0.0567 | 10.0 | 250 | 0.3196 | 0.9075 |
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| 0.0109 | 12.0 | 300 | 0.3644 | 0.9175 |
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| 0.0109 | 14.0 | 350 | 0.3501 | 0.93 |
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| 0.0138 | 16.0 | 400 | 0.3569 | 0.9275 |
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| 0.0138 | 18.0 | 450 | 0.3700 | 0.9225 |
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| 0.0006 | 20.0 | 500 | 0.3662 | 0.925 |
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| 0.0006 | 22.0 | 550 | 0.3669 | 0.925 |
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| 0.0002 | 24.0 | 600 | 0.3673 | 0.925 |
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| 0.0002 | 26.0 | 650 | 0.3677 | 0.925 |
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| 0.0002 | 28.0 | 700 | 0.3679 | 0.9275 |
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| 0.0002 | 30.0 | 750 | 0.3680 | 0.9275 |
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| 0.0002 | 32.0 | 800 | 0.3681 | 0.9275 |
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| 0.0002 | 34.0 | 850 | 0.3684 | 0.9275 |
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| 0.0002 | 36.0 | 900 | 0.3683 | 0.9275 |
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| 0.0002 | 38.0 | 950 | 0.3684 | 0.9275 |
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| 0.0002 | 40.0 | 1000 | 0.3684 | 0.9275 |
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### Framework versions
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- Transformers 4.27.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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