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---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2
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.
It achieves the following results on the evaluation set:
- Loss: 0.6899
- Accuracy: 0.9643
- Precision: 0.9694
- Recall: 0.9643
- F1: 0.9631
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.0165 | 1.0 | 28 | 1.6252 | 0.4643 | 0.5373 | 0.4643 | 0.4711 |
| 1.3702 | 2.0 | 56 | 1.0553 | 0.8571 | 0.8929 | 0.8571 | 0.8536 |
| 0.8861 | 3.0 | 84 | 0.6899 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.5655 | 4.0 | 112 | 0.4766 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.4232 | 5.0 | 140 | 0.3403 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.3148 | 6.0 | 168 | 0.2679 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.2335 | 7.0 | 196 | 0.2239 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.176 | 8.0 | 224 | 0.1979 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.1624 | 9.0 | 252 | 0.1824 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
| 0.1466 | 10.0 | 280 | 0.1781 | 0.9643 | 0.9694 | 0.9643 | 0.9631 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.11.0
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