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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
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