transformers safetensors distilbert text-classification generated_from_trainer en dataset:Henriquee/CarEvaluationDataset base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert/distilbert-base-uncased
datasets:
- Henriquee/CarEvaluationDataset
language:
- en
license: apache-2.0
metrics:
- f1
- accuracy
- roc auc
pipeline_tag: text-classification
tags:
- generated_from_trainer
widget:
- text: The buying price of a car is very high and its cost of maintenance is very
    high, the car has 2 doors, it can accommodate 2 persons, has a small luggage size,
    and the car safety rating is high.
  example_title: '"Unacceptable" example'
- text: The buying price of a car is high and its cost of maintenance is med, the
    car has 5 doors, it can accommodate 5 persons, has a small luggage size, and the
    car safety rating is high.
  example_title: '"Acceptable" example'
- text: The buying price of a car is med and its cost of maintenance is low, the car
    has 5 doors, it can accommodate 4 persons, has a big luggage size, and the car
    safety rating is med.
  example_title: '"Good" example'
- text: The buying price of a car is low and its cost of maintenance is low, the car
    has 5 doors, it can accommodate 4 persons, has a med luggage size, and the car
    safety rating is high.
  example_title: '"Very Good" example'
model-index:
- name: bert-text-classification-car-evaluation
  results:
  - task:
      type: text-classification
    dataset:
      name: Henriquee/CarEvaluationDataset
      type: Henriquee/CarEvaluationDataset
    metrics:
    - type: f1
      value: 1.0
      name: f1
      verified: true
    - type: accuracy
      value: 1.0
      name: accuracy
      verified: true
    - type: roc auc
      value: 1.0
      name: roc auc
      verified: true
---

<!-- 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-text-classification-car-evaluation

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the 
[Car Evaluation Dataset](https://huggingface.co/datasets/Henriquee/CarEvaluationDataset). You can always find it 
[here](https://huggingface.co/datasets/Henriquee/CarEvaluationDataset) in Hugging Face Hub.

It achieves the following results on the evaluation set:
- Loss: 0.0090
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0

## Model description

The model is designed for text classification tasks on the Car Evaluation Dataset. It is a fine-tuned version of the DistilBERT model, 
aiming to predict car evaluation categories based on textual information.

## Intended uses & limitations

### Intended Uses
* Car evaluation category prediction based on textual information.
* Text classification tasks related to the car evaluation domain.

### Limitations
* The model's performance is specifically tuned for the Car Evaluation Dataset; its generalization to other tasks or datasets might be
* limited.
* It may not perform optimally on text from different domains or with substantially different linguistic characteristics.

## Training and evaluation data

The model was trained on the Car Evaluation Dataset, which includes textual descriptions of cars along with corresponding evaluation 
categories.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- early_stopping: 10

### Training results

The model stopped training at the 29th epoch, achieving the following results on the evaluation set:

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.469         | 1.0   | 33   | 0.3870          | 0.6812 | 0.7874  | 0.6812   |
| 0.3686        | 2.0   | 66   | 0.3724          | 0.6812 | 0.7874  | 0.6812   |
| 0.3455        | 3.0   | 99   | 0.3243          | 0.6921 | 0.7787  | 0.6058   |
| 0.2809        | 4.0   | 132  | 0.2348          | 0.8148 | 0.8720  | 0.7971   |
| 0.1939        | 5.0   | 165  | 0.1762          | 0.8571 | 0.9034  | 0.8522   |
| 0.1609        | 6.0   | 198  | 0.1655          | 0.8734 | 0.9145  | 0.8696   |
| 0.1395        | 7.0   | 231  | 0.1302          | 0.9163 | 0.9406  | 0.9043   |
| 0.1261        | 8.0   | 264  | 0.1133          | 0.9161 | 0.9396  | 0.9014   |
| 0.097         | 9.0   | 297  | 0.1180          | 0.8986 | 0.9324  | 0.8754   |
| 0.0906        | 10.0  | 330  | 0.1212          | 0.9052 | 0.9391  | 0.8870   |
| 0.0851        | 11.0  | 363  | 0.0947          | 0.9078 | 0.9357  | 0.8899   |
| 0.0792        | 12.0  | 396  | 0.0933          | 0.9320 | 0.9551  | 0.9188   |
| 0.073         | 13.0  | 429  | 0.0783          | 0.9277 | 0.9527  | 0.9217   |
| 0.0586        | 14.0  | 462  | 0.0737          | 0.9577 | 0.9696  | 0.9420   |
| 0.0682        | 15.0  | 495  | 0.0855          | 0.9312 | 0.9512  | 0.9188   |
| 0.0625        | 16.0  | 528  | 0.0869          | 0.9391 | 0.9594  | 0.9246   |
| 0.0567        | 17.0  | 561  | 0.0653          | 0.9525 | 0.9705  | 0.9420   |
| 0.0513        | 18.0  | 594  | 0.0576          | 0.9666 | 0.9773  | 0.9565   |
| 0.0463        | 19.0  | 627  | 0.0655          | 0.9595 | 0.9739  | 0.9449   |
| 0.047         | 20.0  | 660  | 0.0485          | 0.9608 | 0.9734  | 0.9478   |
| 0.0379        | 21.0  | 693  | 0.0406          | 0.9825 | 0.9855  | 0.9739   |
| 0.0338        | 22.0  | 726  | 0.0274          | 0.9827 | 0.9894  | 0.9739   |
| 0.0325        | 23.0  | 759  | 0.0215          | 0.9942 | 0.9952  | 0.9913   |
| 0.0254        | 24.0  | 792  | 0.0251          | 0.9913 | 0.9932  | 0.9884   |
| 0.0266        | 25.0  | 825  | 0.0212          | 0.9884 | 0.9923  | 0.9826   |
| 0.0203        | 26.0  | 858  | 0.0170          | 0.9913 | 0.9932  | 0.9884   |
| 0.0193        | 27.0  | 891  | 0.0149          | 0.9986 | 0.9995  | 0.9971   |
| 0.0204        | 28.0  | 924  | 0.0140          | 0.9971 | 0.9971  | 0.9942   |
| 0.0162        | 29.0  | 957  | 0.0094          | 1.0    | 1.0     | 1.0      |
| 0.0157        | 30.0  | 990  | 0.0103          | 1.0    | 1.0     | 1.0      |
| 0.0139        | 31.0  | 1023 | 0.0084          | 1.0    | 1.0     | 1.0      |
| 0.0125        | 32.0  | 1056 | 0.0076          | 1.0    | 1.0     | 1.0      |
| 0.0105        | 33.0  | 1089 | 0.0067          | 1.0    | 1.0     | 1.0      |
| 0.0091        | 34.0  | 1122 | 0.0058          | 1.0    | 1.0     | 1.0      |
| 0.009         | 35.0  | 1155 | 0.0064          | 1.0    | 1.0     | 1.0      |
| 0.0081        | 36.0  | 1188 | 0.0053          | 1.0    | 1.0     | 1.0      |
| 0.0074        | 37.0  | 1221 | 0.0050          | 1.0    | 1.0     | 1.0      |
| 0.008         | 38.0  | 1254 | 0.0050          | 1.0    | 1.0     | 1.0      |
| 0.0077        | 39.0  | 1287 | 0.0053          | 1.0    | 1.0     | 1.0      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2


## Acknowledgments

This model is built upon the [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) pre-trained model and utilizes the Hugging Face Transformers library. 
Special thanks to the creators of the Car Evaluation Dataset for providing the training and evaluation data.

## Contact Information

For any questions or inquiries, please contact the model developer:

Name: Henriquee

Hugging Face: Henriquee

### License

This model is released under the MIT License. See the LICENSE file for more details.