---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
- accuracy
- f1
model-index:
- name: lora_fine_tuned_boolq
  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. -->

# lora_fine_tuned_boolq

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5547
- Accuracy: 0.7778
- F1: 0.6806

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6762        | 4.1667  | 50   | 0.5947          | 0.7778   | 0.6806 |
| 0.6639        | 8.3333  | 100  | 0.5719          | 0.7778   | 0.6806 |
| 0.6555        | 12.5    | 150  | 0.5648          | 0.7778   | 0.6806 |
| 0.6605        | 16.6667 | 200  | 0.5615          | 0.7778   | 0.6806 |
| 0.6612        | 20.8333 | 250  | 0.5568          | 0.7778   | 0.6806 |
| 0.6508        | 25.0    | 300  | 0.5567          | 0.7778   | 0.6806 |
| 0.6491        | 29.1667 | 350  | 0.5550          | 0.7778   | 0.6806 |
| 0.663         | 33.3333 | 400  | 0.5547          | 0.7778   | 0.6806 |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1