---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_copa_bert
  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_copa_bert

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: 1.0295
- Accuracy: 0.54
- F1: 0.5407

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7066        | 1.0   | 50   | 0.6907          | 0.54     | 0.5411 |
| 0.6897        | 2.0   | 100  | 0.6880          | 0.57     | 0.5709 |
| 0.6001        | 3.0   | 150  | 0.7025          | 0.55     | 0.5511 |
| 0.4629        | 4.0   | 200  | 0.7810          | 0.53     | 0.5310 |
| 0.3402        | 5.0   | 250  | 1.0003          | 0.55     | 0.5511 |
| 0.2299        | 6.0   | 300  | 1.0220          | 0.55     | 0.5511 |
| 0.1874        | 7.0   | 350  | 0.9956          | 0.56     | 0.5611 |
| 0.1133        | 8.0   | 400  | 1.0295          | 0.54     | 0.5407 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1