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  ---
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- license: bsd-3-clause
 
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  tags:
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- - audio-classification
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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 bookbot/audioset 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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-
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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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-
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-
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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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  ---
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+ language: en
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+ license: apache-2.0
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  tags:
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+ - audio-classification
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+ - generated_from_trainer
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  metrics:
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+ - accuracy
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+ - f1
 
 
 
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  ---
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+ # Distil Audio Spectrogram Transformer AudioSet
 
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+ Distil Audio Spectrogram Transformer AudioSet is an audio classification model based on the [Audio Spectrogram Transformer](https://arxiv.org/abs/2104.01778) architecture. This model is a distilled version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the [AudioSet](https://research.google.com/audioset/download.html) dataset.
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+ This model was trained using HuggingFace's PyTorch framework. All training was done on a Google Cloud Engine VM with a Tesla A100 GPU. All necessary scripts used for training could be found in the [Files and versions](https://huggingface.co/bookbot/distil-ast-audioset/tree/main) tab, as well as the [Training metrics](https://huggingface.co/bookbot/distil-ast-audioset/tensorboard) logged via Tensorboard.
 
 
 
 
 
 
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+ ## Model
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+ | Model | #params | Arch. | Training/Validation data |
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+ | --------------------- | ------- | ----------------------------- | ------------------------ |
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+ | `distil-ast-audioset` | 44M | Audio Spectrogram Transformer | AudioSet |
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+ ## Evaluation Results
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+ The model achieves the following results on evaluation:
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+ | Model | F1 | Roc Auc | Accuracy | mAP |
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+ | ------------------- | ------ | ------- | -------- | ------ |
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+ | Distil-AST AudioSet | 0.4876 | 0.7140 | 0.0714 | 0.4743 |
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+ | AST AudioSet | 0.4989 | 0.6905 | 0.1247 | 0.5603 |
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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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+
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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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+
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+ ## Disclaimer
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+
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+ Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.
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+
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+ ## Authors
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+
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+ Distil Audio Spectrogram Transformer AudioSet was trained and evaluated by [Ananto Joyoadikusumo](https://anantoj.github.io), [David Samuel Setiawan](https://davidsamuell.github.io/), [Wilson Wongso](https://wilsonwongso.dev/). All computation and development are done on Google Cloud.
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+
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+ ## Framework versions
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  - Transformers 4.27.0.dev0
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  - Pytorch 1.13.1+cu117