transformers tensorboard safetensors audio-spectrogram-transformer audio-classification generated_from_trainer base_model:MIT/ast-finetuned-audioset-10-10-0.4593 license:bsd-3-clause endpoints_compatible region:us
---
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: []
---

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# 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
