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alimazhar-110
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website_classification

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
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website_classification / README.md
Ali Mazhar Luqmani
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: website_classification
    results: []

website_classification

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2909
  • Accuracy: 0.9362
  • F1: 0.9354
  • Precision: 0.9380
  • Recall: 0.9362

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
2.4251 1.0 71 1.8259 0.8688 0.8615 0.8645 0.8688
1.34 2.0 142 0.8796 0.9078 0.8978 0.8929 0.9078
0.6342 3.0 213 0.5158 0.9113 0.9052 0.9078 0.9113
0.3265 4.0 284 0.3381 0.9326 0.9268 0.9254 0.9326
0.165 5.0 355 0.3140 0.9255 0.9201 0.9215 0.9255
0.0939 6.0 426 0.2805 0.9291 0.9252 0.9279 0.9291
0.0568 7.0 497 0.2679 0.9362 0.9308 0.9290 0.9362
0.0337 8.0 568 0.2728 0.9291 0.9227 0.9217 0.9291
0.0216 9.0 639 0.2531 0.9362 0.9355 0.9379 0.9362
0.0141 10.0 710 0.2741 0.9326 0.9325 0.9362 0.9326
0.0108 11.0 781 0.2749 0.9291 0.9278 0.9302 0.9291
0.0086 12.0 852 0.2680 0.9291 0.9278 0.9302 0.9291
0.0074 13.0 923 0.2688 0.9326 0.9303 0.9317 0.9326
0.0065 14.0 994 0.2736 0.9362 0.9354 0.9380 0.9362
0.0057 15.0 1065 0.2780 0.9362 0.9354 0.9380 0.9362
0.0051 16.0 1136 0.2730 0.9362 0.9323 0.9321 0.9362
0.0047 17.0 1207 0.2793 0.9362 0.9344 0.9361 0.9362
0.0044 18.0 1278 0.2784 0.9362 0.9354 0.9380 0.9362
0.0039 19.0 1349 0.2799 0.9362 0.9354 0.9380 0.9362
0.0036 20.0 1420 0.2820 0.9362 0.9354 0.9380 0.9362
0.0035 21.0 1491 0.2836 0.9362 0.9354 0.9380 0.9362
0.0032 22.0 1562 0.2851 0.9362 0.9354 0.9380 0.9362
0.0032 23.0 1633 0.2863 0.9362 0.9354 0.9380 0.9362
0.0031 24.0 1704 0.2901 0.9362 0.9354 0.9380 0.9362
0.0029 25.0 1775 0.2896 0.9362 0.9354 0.9380 0.9362
0.0028 26.0 1846 0.2892 0.9362 0.9354 0.9380 0.9362
0.0027 27.0 1917 0.2891 0.9362 0.9354 0.9380 0.9362
0.0026 28.0 1988 0.2898 0.9362 0.9354 0.9380 0.9362
0.0027 29.0 2059 0.2909 0.9362 0.9354 0.9380 0.9362
0.0026 30.0 2130 0.2909 0.9362 0.9354 0.9380 0.9362

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2