| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: website_classification |
| | 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. --> |
| |
|
| | # website_classification |
| | |
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2292 |
| | - Accuracy: 0.9504 |
| | - F1: 0.9489 |
| | - Precision: 0.9510 |
| | - Recall: 0.9504 |
| | |
| | ## 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: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 2.404 | 1.0 | 71 | 1.7840 | 0.8865 | 0.8776 | 0.8785 | 0.8865 | |
| | | 1.295 | 2.0 | 142 | 0.8539 | 0.8972 | 0.8871 | 0.8803 | 0.8972 | |
| | | 0.6186 | 3.0 | 213 | 0.4818 | 0.9326 | 0.9263 | 0.9266 | 0.9326 | |
| | | 0.3103 | 4.0 | 284 | 0.3101 | 0.9397 | 0.9343 | 0.9324 | 0.9397 | |
| | | 0.1618 | 5.0 | 355 | 0.3001 | 0.9291 | 0.9251 | 0.9278 | 0.9291 | |
| | | 0.0893 | 6.0 | 426 | 0.2743 | 0.9291 | 0.9251 | 0.9276 | 0.9291 | |
| | | 0.0547 | 7.0 | 497 | 0.2605 | 0.9255 | 0.9236 | 0.9334 | 0.9255 | |
| | | 0.028 | 8.0 | 568 | 0.2167 | 0.9397 | 0.9375 | 0.9403 | 0.9397 | |
| | | 0.0186 | 9.0 | 639 | 0.2096 | 0.9468 | 0.9467 | 0.9499 | 0.9468 | |
| | | 0.0134 | 10.0 | 710 | 0.2219 | 0.9362 | 0.9354 | 0.9402 | 0.9362 | |
| | | 0.0107 | 11.0 | 781 | 0.2124 | 0.9468 | 0.9466 | 0.9507 | 0.9468 | |
| | | 0.0087 | 12.0 | 852 | 0.2119 | 0.9504 | 0.9497 | 0.9534 | 0.9504 | |
| | | 0.0075 | 13.0 | 923 | 0.2141 | 0.9504 | 0.9497 | 0.9534 | 0.9504 | |
| | | 0.0066 | 14.0 | 994 | 0.2198 | 0.9433 | 0.9415 | 0.9442 | 0.9433 | |
| | | 0.0058 | 15.0 | 1065 | 0.2188 | 0.9468 | 0.9454 | 0.9474 | 0.9468 | |
| | | 0.0052 | 16.0 | 1136 | 0.2181 | 0.9468 | 0.9454 | 0.9474 | 0.9468 | |
| | | 0.0047 | 17.0 | 1207 | 0.2220 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.0044 | 18.0 | 1278 | 0.2232 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.004 | 19.0 | 1349 | 0.2216 | 0.9539 | 0.9535 | 0.9565 | 0.9539 | |
| | | 0.0037 | 20.0 | 1420 | 0.2251 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.0036 | 21.0 | 1491 | 0.2275 | 0.9468 | 0.9451 | 0.9470 | 0.9468 | |
| | | 0.0034 | 22.0 | 1562 | 0.2264 | 0.9539 | 0.9535 | 0.9565 | 0.9539 | |
| | | 0.0032 | 23.0 | 1633 | 0.2283 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.003 | 24.0 | 1704 | 0.2299 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.0029 | 25.0 | 1775 | 0.2282 | 0.9468 | 0.9451 | 0.9470 | 0.9468 | |
| | | 0.0029 | 26.0 | 1846 | 0.2288 | 0.9468 | 0.9451 | 0.9470 | 0.9468 | |
| | | 0.0028 | 27.0 | 1917 | 0.2286 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.0027 | 28.0 | 1988 | 0.2293 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.0026 | 29.0 | 2059 | 0.2291 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | | 0.0026 | 30.0 | 2130 | 0.2292 | 0.9504 | 0.9489 | 0.9510 | 0.9504 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.0 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.9.0 |
| | - Tokenizers 0.13.2 |
| | |
