---
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: 0.6912
- Accuracy: 0.7347

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.02          | 1.0   | 1150 | 0.8192          | 0.6860   |
| 0.9222        | 2.0   | 2300 | 0.7436          | 0.7128   |
| 0.8859        | 3.0   | 3450 | 0.7166          | 0.7247   |
| 0.8639        | 4.0   | 4600 | 0.7008          | 0.7295   |
| 0.8689        | 5.0   | 5750 | 0.6954          | 0.7335   |
| 0.8639        | 6.0   | 6900 | 0.6912          | 0.7347   |


### Framework versions

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