| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: distilbert/distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: text_highlighting_model |
| | 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. --> |
| |
|
| | # text_highlighting_model |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2861 |
| | - Precision: 0.8591 |
| | - Recall: 0.8873 |
| | - F1: 0.8730 |
| | - Accuracy: 0.8931 |
| |
|
| | ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | 0.3105 | 1.0 | 937 | 0.2707 | 0.8204 | 0.9062 | 0.8611 | 0.8790 | |
| | | 0.2547 | 2.0 | 1874 | 0.2559 | 0.8466 | 0.8819 | 0.8639 | 0.8849 | |
| | | 0.2354 | 3.0 | 2811 | 0.2517 | 0.8565 | 0.8762 | 0.8663 | 0.8880 | |
| | | 0.2171 | 4.0 | 3748 | 0.2584 | 0.8496 | 0.8921 | 0.8703 | 0.8900 | |
| | | 0.201 | 5.0 | 4685 | 0.2575 | 0.8492 | 0.8963 | 0.8721 | 0.8912 | |
| | | 0.1875 | 6.0 | 5622 | 0.2636 | 0.8501 | 0.8967 | 0.8728 | 0.8918 | |
| | | 0.1782 | 7.0 | 6559 | 0.2691 | 0.8625 | 0.8804 | 0.8714 | 0.8924 | |
| | | 0.1686 | 8.0 | 7496 | 0.2778 | 0.8540 | 0.8948 | 0.8739 | 0.8931 | |
| | | 0.1623 | 9.0 | 8433 | 0.2801 | 0.8594 | 0.8867 | 0.8728 | 0.8930 | |
| | | 0.1581 | 10.0 | 9370 | 0.2861 | 0.8591 | 0.8873 | 0.8730 | 0.8931 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.53.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 4.4.1 |
| | - Tokenizers 0.21.2 |
| |
|
