---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine-tuned-bert-base-uncased-swag
  results: []
datasets:
- allenai/swag
---

<!-- 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. -->

# fine-tuned-bert-base-uncased-swag

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on SWAG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5259
- Accuracy: 0.8134

## 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: 1.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7736        | 1.0   | 1150 | 0.5534          | 0.7911   |
| 0.5913        | 2.0   | 2300 | 0.5009          | 0.8086   |
| 0.4462        | 3.0   | 3450 | 0.5014          | 0.8122   |
| 0.3695        | 4.0   | 4600 | 0.5259          | 0.8134   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1