---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavLM-base-DeepFake_UTCN
  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. -->

# wavLM-base-DeepFake_UTCN

This model is a fine-tuned version of [microsoft/wavLM-base](https://huggingface.co/microsoft/wavLM-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9119
- Accuracy: 0.73

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0316        | 1.0   | 281  | 1.0076          | 0.6022   |
| 0.0486        | 2.0   | 562  | 1.2997          | 0.4522   |
| 0.0788        | 3.0   | 843  | 1.1793          | 0.6089   |
| 0.0559        | 4.0   | 1125 | 1.0675          | 0.6678   |
| 0.0396        | 5.0   | 1405 | 0.9119          | 0.73     |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3