---
license: apache-2.0
base_model: asapp/sew-mid-100k
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sew-ft-fake-detection
  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. -->

# sew-ft-fake-detection

This model is a fine-tuned version of [asapp/sew-mid-100k](https://huggingface.co/asapp/sew-mid-100k) on the alexandreacff/kaggle-fake-detection dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6232
- Accuracy: 0.7439

## 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: 32
- eval_batch_size: 16
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6344        | 0.9851 | 33   | 0.6395          | 0.6505   |
| 0.6157        | 2.0    | 67   | 0.6703          | 0.5215   |
| 0.5572        | 2.9851 | 100  | 0.5615          | 0.7131   |
| 0.4968        | 4.0    | 134  | 0.8149          | 0.6944   |
| 0.4988        | 4.9851 | 167  | 0.8099          | 0.7037   |
| 0.4756        | 6.0    | 201  | 0.8319          | 0.7103   |
| 0.4334        | 6.9851 | 234  | 0.7317          | 0.7336   |
| 0.4321        | 8.0    | 268  | 0.6548          | 0.7383   |
| 0.4436        | 8.9851 | 301  | 0.6232          | 0.7439   |
| 0.4493        | 9.8507 | 330  | 0.6278          | 0.7439   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.19.1
- Tokenizers 0.19.1