---
license: mit
tags:
- generated_from_trainer
datasets:
- feverous
metrics:
- accuracy
model-index:
- name: deberta-v3-base-finetuned-fever
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: feverous
      type: feverous
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6153358681875792
---

<!-- 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. -->

# deberta-v3-base-finetuned-fever

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the feverous dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8830
- Accuracy: 0.6153

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7054        | 1.0   | 4456  | 0.8351          | 0.6027   |
| 0.6389        | 2.0   | 8912  | 0.8830          | 0.6153   |
| 0.5562        | 3.0   | 13368 | 0.9398          | 0.6134   |
| 0.4614        | 4.0   | 17824 | 1.0787          | 0.6115   |
| 0.3867        | 5.0   | 22280 | 1.1430          | 0.6091   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3