README.md

---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-AST
  results: []
---

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# ast-finetuned-audioset-10-10-0.4593-finetuned-AST

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: 0.3787
- Accuracy: 0.9463
- F1: 0.9426

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7914        | 1.0   | 1467 | 0.5058          | 0.8788   | 0.8679 |
| 0.5962        | 2.0   | 2934 | 0.4318          | 0.9018   | 0.8941 |
| 0.0143        | 3.0   | 4401 | 0.4418          | 0.9233   | 0.9183 |
| 0.0002        | 4.0   | 5868 | 0.3996          | 0.9387   | 0.9342 |
| 0.0001        | 5.0   | 7335 | 0.3787          | 0.9463   | 0.9426 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3