README.md

---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
- NLP Regression
- Regression
- Edmunds Car Reviews
model-index:
- name: bert-base-uncased-Regression-Edmunds_Car_Reviews
  results: []
language:
- en
metrics:
- mse
- mae
---

# bert-base-uncased-Regression-Edmunds_Car_Reviews

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased).

It achieves the following results on the evaluation set:
- Loss: 0.2324
- Mse: 0.2324
- Rmse: 0.4820
- Mae: 0.3089

## Model description

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/NLP%20Regression/Edmunds%20Car%20Reviews%20(BERT-Base)/Edmunds_Consumer_car_Regression_All_Manufacturers_Bert_Base.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/ankkur13/edmundsconsumer-car-ratings-and-reviews

## 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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Rmse   | Mae    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
| 0.2142        | 1.0   | 11430 | 0.2421          | 0.2421 | 0.4920 | 0.3126 |
| 0.1931        | 2.0   | 22860 | 0.2530          | 0.2530 | 0.5030 | 0.3336 |
| 0.1192        | 3.0   | 34290 | 0.2324          | 0.2324 | 0.4820 | 0.3089 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3