---
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_copa
  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_copa

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: 0.6918
- Accuracy: 0.46
- F1: 0.4570

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7088        | 1.0   | 50   | 0.6921          | 0.48     | 0.48   |
| 0.7024        | 2.0   | 100  | 0.6922          | 0.49     | 0.4894 |
| 0.6993        | 3.0   | 150  | 0.6921          | 0.46     | 0.4587 |
| 0.7005        | 4.0   | 200  | 0.6920          | 0.48     | 0.4788 |
| 0.6989        | 5.0   | 250  | 0.6919          | 0.47     | 0.4679 |
| 0.7018        | 6.0   | 300  | 0.6919          | 0.46     | 0.4570 |
| 0.6943        | 7.0   | 350  | 0.6919          | 0.46     | 0.4570 |
| 0.6943        | 8.0   | 400  | 0.6918          | 0.46     | 0.4570 |


### Framework versions

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