---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- swag
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-swag-mcq
  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. -->

# bert-base-uncased-finetuned-swag-mcq

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the swag dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9458
- Accuracy: 0.8055

## 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7305        | 1.0   | 4597  | 0.5244          | 0.7958   |
| 0.4343        | 2.0   | 9194  | 0.5315          | 0.8081   |
| 0.2468        | 3.0   | 13791 | 0.7024          | 0.8048   |
| 0.1334        | 4.0   | 18388 | 0.9458          | 0.8055   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3