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website_classification

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: website_classification
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # website_classification
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2909
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+ - Accuracy: 0.9362
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+ - F1: 0.9354
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+ - Precision: 0.9380
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+ - Recall: 0.9362
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 2.4251 | 1.0 | 71 | 1.8259 | 0.8688 | 0.8615 | 0.8645 | 0.8688 |
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+ | 1.34 | 2.0 | 142 | 0.8796 | 0.9078 | 0.8978 | 0.8929 | 0.9078 |
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+ | 0.6342 | 3.0 | 213 | 0.5158 | 0.9113 | 0.9052 | 0.9078 | 0.9113 |
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+ | 0.3265 | 4.0 | 284 | 0.3381 | 0.9326 | 0.9268 | 0.9254 | 0.9326 |
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+ | 0.165 | 5.0 | 355 | 0.3140 | 0.9255 | 0.9201 | 0.9215 | 0.9255 |
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+ | 0.0939 | 6.0 | 426 | 0.2805 | 0.9291 | 0.9252 | 0.9279 | 0.9291 |
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+ | 0.0568 | 7.0 | 497 | 0.2679 | 0.9362 | 0.9308 | 0.9290 | 0.9362 |
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+ | 0.0337 | 8.0 | 568 | 0.2728 | 0.9291 | 0.9227 | 0.9217 | 0.9291 |
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+ | 0.0216 | 9.0 | 639 | 0.2531 | 0.9362 | 0.9355 | 0.9379 | 0.9362 |
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+ | 0.0141 | 10.0 | 710 | 0.2741 | 0.9326 | 0.9325 | 0.9362 | 0.9326 |
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+ | 0.0108 | 11.0 | 781 | 0.2749 | 0.9291 | 0.9278 | 0.9302 | 0.9291 |
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+ | 0.0086 | 12.0 | 852 | 0.2680 | 0.9291 | 0.9278 | 0.9302 | 0.9291 |
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+ | 0.0074 | 13.0 | 923 | 0.2688 | 0.9326 | 0.9303 | 0.9317 | 0.9326 |
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+ | 0.0065 | 14.0 | 994 | 0.2736 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0057 | 15.0 | 1065 | 0.2780 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0051 | 16.0 | 1136 | 0.2730 | 0.9362 | 0.9323 | 0.9321 | 0.9362 |
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+ | 0.0047 | 17.0 | 1207 | 0.2793 | 0.9362 | 0.9344 | 0.9361 | 0.9362 |
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+ | 0.0044 | 18.0 | 1278 | 0.2784 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0039 | 19.0 | 1349 | 0.2799 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0036 | 20.0 | 1420 | 0.2820 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0035 | 21.0 | 1491 | 0.2836 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0032 | 22.0 | 1562 | 0.2851 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0032 | 23.0 | 1633 | 0.2863 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0031 | 24.0 | 1704 | 0.2901 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0029 | 25.0 | 1775 | 0.2896 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0028 | 26.0 | 1846 | 0.2892 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0027 | 27.0 | 1917 | 0.2891 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0026 | 28.0 | 1988 | 0.2898 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0027 | 29.0 | 2059 | 0.2909 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+ | 0.0026 | 30.0 | 2130 | 0.2909 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2