---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FakeNews-deberta-base-punct
  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. -->

# FakeNews-deberta-base-punct

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co./microsoft/deberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4681
- Accuracy: 0.8374

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.54          | 1.0   | 1605 | 0.4681          | 0.8374   |
| 0.7002        | 2.0   | 3210 | 0.7113          | 0.5234   |
| 0.6967        | 3.0   | 4815 | 0.6938          | 0.5234   |
| 0.6961        | 4.0   | 6420 | 0.6959          | 0.4766   |
| 0.6935        | 5.0   | 8025 | 0.6921          | 0.5234   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1