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

# loha_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: 0.6922
- Accuracy: 0.5
- F1: 0.5

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
| 0.7089        | 1.0   | 50   | 0.6923          | 0.5      | 0.5 |
| 0.7026        | 2.0   | 100  | 0.6923          | 0.5      | 0.5 |
| 0.6995        | 3.0   | 150  | 0.6923          | 0.5      | 0.5 |
| 0.7009        | 4.0   | 200  | 0.6923          | 0.5      | 0.5 |
| 0.6997        | 5.0   | 250  | 0.6923          | 0.5      | 0.5 |
| 0.7028        | 6.0   | 300  | 0.6922          | 0.5      | 0.5 |
| 0.6951        | 7.0   | 350  | 0.6922          | 0.5      | 0.5 |
| 0.6949        | 8.0   | 400  | 0.6922          | 0.5      | 0.5 |


### Framework versions

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