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---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gunshot
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-finetuned-gunshot
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: 0.8795
- Accuracy: 0.7529
## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0609 | 1.0 | 341 | 1.3465 | 0.6588 |
| 2.5693 | 2.0 | 682 | 1.3427 | 0.6882 |
| 0.3521 | 3.0 | 1023 | 0.7226 | 0.7647 |
| 0.4897 | 4.0 | 1364 | 0.3091 | 0.8471 |
| 0.2211 | 5.0 | 1705 | 0.5495 | 0.8235 |
| 0.1775 | 6.0 | 2046 | 0.3732 | 0.8235 |
| 0.1227 | 7.0 | 2387 | 0.3936 | 0.7882 |
| 0.0661 | 8.0 | 2728 | 0.8744 | 0.7412 |
| 0.1584 | 9.0 | 3069 | 0.7891 | 0.7647 |
| 0.0707 | 10.0 | 3410 | 0.8795 | 0.7529 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.15.1.dev0
- Tokenizers 0.15.0
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