---
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