---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer
  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. -->

# trainer

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3684
- Accuracy: 0.9275

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.2624        | 2.0   | 50   | 0.3928          | 0.88     |
| 0.9069        | 4.0   | 100  | 0.3259          | 0.9025   |
| 0.9069        | 6.0   | 150  | 0.2775          | 0.93     |
| 0.0567        | 8.0   | 200  | 0.3220          | 0.9075   |
| 0.0567        | 10.0  | 250  | 0.3196          | 0.9075   |
| 0.0109        | 12.0  | 300  | 0.3644          | 0.9175   |
| 0.0109        | 14.0  | 350  | 0.3501          | 0.93     |
| 0.0138        | 16.0  | 400  | 0.3569          | 0.9275   |
| 0.0138        | 18.0  | 450  | 0.3700          | 0.9225   |
| 0.0006        | 20.0  | 500  | 0.3662          | 0.925    |
| 0.0006        | 22.0  | 550  | 0.3669          | 0.925    |
| 0.0002        | 24.0  | 600  | 0.3673          | 0.925    |
| 0.0002        | 26.0  | 650  | 0.3677          | 0.925    |
| 0.0002        | 28.0  | 700  | 0.3679          | 0.9275   |
| 0.0002        | 30.0  | 750  | 0.3680          | 0.9275   |
| 0.0002        | 32.0  | 800  | 0.3681          | 0.9275   |
| 0.0002        | 34.0  | 850  | 0.3684          | 0.9275   |
| 0.0002        | 36.0  | 900  | 0.3683          | 0.9275   |
| 0.0002        | 38.0  | 950  | 0.3684          | 0.9275   |
| 0.0002        | 40.0  | 1000 | 0.3684          | 0.9275   |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3