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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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- f1
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- accuracy
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model-index:
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- name: distil-ast-audioset-2
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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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# distil-ast-audioset-2
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3063
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- F1: 0.4876
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- Roc Auc: 0.7140
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- Accuracy: 0.0714
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- Map: 0.4743
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 0
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 10.0
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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 | F1 | Roc Auc | Accuracy | Map |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------:|
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| 1.5521 | 1.0 | 153 | 0.7759 | 0.3929 | 0.6789 | 0.0209 | 0.3394 |
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| 0.7088 | 2.0 | 306 | 0.5183 | 0.4480 | 0.7162 | 0.0349 | 0.4047 |
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| 0.484 | 3.0 | 459 | 0.4342 | 0.4673 | 0.7241 | 0.0447 | 0.4348 |
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| 0.369 | 4.0 | 612 | 0.3847 | 0.4777 | 0.7332 | 0.0504 | 0.4463 |
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| 0.2943 | 5.0 | 765 | 0.3587 | 0.4838 | 0.7284 | 0.0572 | 0.4556 |
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| 0.2446 | 6.0 | 918 | 0.3415 | 0.4875 | 0.7296 | 0.0608 | 0.4628 |
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| 0.2099 | 7.0 | 1071 | 0.3273 | 0.4896 | 0.7246 | 0.0648 | 0.4682 |
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| 0.186 | 8.0 | 1224 | 0.3140 | 0.4888 | 0.7171 | 0.0689 | 0.4711 |
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| 0.1693 | 9.0 | 1377 | 0.3101 | 0.4887 | 0.7157 | 0.0703 | 0.4741 |
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| 0.1582 | 10.0 | 1530 | 0.3063 | 0.4876 | 0.7140 | 0.0714 | 0.4743 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.10.0
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- Tokenizers 0.13.2
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