---
language:
- en
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
datasets:
- swag
metrics:
- accuracy
model-index:
- name: llm-deberta-v3-swag
  results:
  - task:
      name: Multiple Choice
      type: multiple-choice
    dataset:
      name: SWAG
      type: swag
      config: regular
      split: validation
      args: regular
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8679895997047424
---

<!-- 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. -->

# llm-deberta-v3-swag

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the SWAG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7839
- Accuracy: 0.8680

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0