---
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: revix_classifier
  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. -->

# revix_classifier

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: 0.4733
- Accuracy: 0.9292
- Precision: 0.9492
- Recall: 0.9106
- F1: 0.9295

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4055        | 1.0   | 120  | 0.4456          | 0.8      | 0.7698    | 0.8699 | 0.8168 |
| 0.4578        | 2.0   | 240  | 0.4217          | 0.875    | 0.8345    | 0.9431 | 0.8855 |
| 0.2235        | 3.0   | 360  | 0.4959          | 0.85     | 0.9780    | 0.7236 | 0.8318 |
| 0.092         | 4.0   | 480  | 0.3820          | 0.9083   | 0.9391    | 0.8780 | 0.9076 |
| 0.2152        | 5.0   | 600  | 0.5537          | 0.8792   | 0.8615    | 0.9106 | 0.8854 |
| 0.0612        | 6.0   | 720  | 0.4747          | 0.9292   | 0.9417    | 0.9187 | 0.9300 |
| 0.0382        | 7.0   | 840  | 0.4424          | 0.925    | 0.9412    | 0.9106 | 0.9256 |
| 0.0015        | 8.0   | 960  | 0.4647          | 0.925    | 0.9646    | 0.8862 | 0.9237 |
| 0.0005        | 9.0   | 1080 | 0.4684          | 0.9292   | 0.9492    | 0.9106 | 0.9295 |
| 0.0006        | 10.0  | 1200 | 0.4733          | 0.9292   | 0.9492    | 0.9106 | 0.9295 |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0