---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: bert-base-uncased
datasets:
- swag
metrics:
- accuracy
model-index:
- name: fine-tuned-bert-base-uncased-swag-peft
  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. -->

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

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: 0.6557
- Accuracy: 0.7483

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0316        | 1.0   | 1150  | 0.8202          | 0.6860   |
| 0.9261        | 2.0   | 2300  | 0.7423          | 0.7144   |
| 0.8862        | 3.0   | 3450  | 0.7114          | 0.7268   |
| 0.8612        | 4.0   | 4600  | 0.6924          | 0.7347   |
| 0.8637        | 5.0   | 5750  | 0.6819          | 0.7393   |
| 0.8541        | 6.0   | 6900  | 0.6691          | 0.7441   |
| 0.8369        | 7.0   | 8050  | 0.6635          | 0.7464   |
| 0.8349        | 8.0   | 9200  | 0.6591          | 0.7475   |
| 0.8302        | 9.0   | 10350 | 0.6572          | 0.7483   |
| 0.8333        | 10.0  | 11500 | 0.6557          | 0.7483   |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1