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Henriquee/bert-text-classification-car-evaluation
bert-text-classification-car-evaluation is a text classification model from Henriquee. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the Car Evaluation Dataset. You can always find it here in Hugging Face Hub.
It achieves the following results on the evaluation set:
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.
The model was trained on the Car Evaluation Dataset, which includes textual descriptions of cars along with corresponding evaluation categories.
The following hyperparameters were used during training:
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 |
This model is built upon the 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.
For any questions or inquiries, please contact the model developer:
Name: Henriquee
Hugging Face: Henriquee
This model is released under the MIT License. See the LICENSE file for more details.