---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: S1_M1_R2_AST_42783203
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# S1_M1_R2_AST_42783203

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: 0.0000
- Accuracy: 1.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0009        | 1.0   | 309  | 0.0012          | 1.0      |
| 0.0003        | 2.0   | 619  | 0.0002          | 1.0      |
| 0.0           | 3.0   | 929  | 0.0000          | 1.0      |
| 0.0           | 4.0   | 1239 | 0.0000          | 1.0      |
| 0.0           | 4.99  | 1545 | 0.0000          | 1.0      |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3