---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-qqp
  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. -->

# bert-base-cased-finetuned-qqp

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.9109
- Combined Score: 0.8957
- F1: 0.8805
- Loss: 0.3568

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Combined Score | F1     | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:--------------:|:------:|:---------------:|
| 0.2942        | 1.0   | 22741 | 0.9009   | 0.8845         | 0.8681 | 0.2476          |
| 0.1919        | 2.0   | 45482 | 0.9080   | 0.8920         | 0.8761 | 0.2706          |
| 0.1342        | 3.0   | 68223 | 0.9109   | 0.8957         | 0.8805 | 0.3568          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1