---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: distilbert-base-uncased-finetuned-text_cl
  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. -->

# distilbert-base-uncased-finetuned-text_cl

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2450
- Accuracy: 0.8641
- Recall: 0.9482
- Precision: 0.8402
- F1: 0.8910

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 231  | 0.4105          | 0.7765   | 0.9343 | 0.7474    | 0.8305 |
| No log        | 2.0   | 462  | 0.5147          | 0.7946   | 0.9741 | 0.75      | 0.8475 |
| 0.2425        | 3.0   | 693  | 0.3620          | 0.8407   | 0.9373 | 0.8175    | 0.8733 |
| 0.2425        | 4.0   | 924  | 0.5248          | 0.8646   | 0.9402 | 0.8459    | 0.8906 |
| 0.0988        | 5.0   | 1155 | 0.7085          | 0.8553   | 0.9492 | 0.8287    | 0.8849 |
| 0.0988        | 6.0   | 1386 | 0.7420          | 0.8652   | 0.9084 | 0.8677    | 0.8876 |
| 0.0284        | 7.0   | 1617 | 0.7172          | 0.8705   | 0.9442 | 0.8510    | 0.8952 |
| 0.0284        | 8.0   | 1848 | 0.8150          | 0.8681   | 0.9442 | 0.8479    | 0.8935 |
| 0.0084        | 9.0   | 2079 | 0.9139          | 0.8629   | 0.9373 | 0.8455    | 0.8890 |
| 0.0084        | 10.0  | 2310 | 0.9463          | 0.8571   | 0.9392 | 0.8367    | 0.8850 |
| 0.009         | 11.0  | 2541 | 0.9524          | 0.8658   | 0.9124 | 0.8658    | 0.8885 |
| 0.009         | 12.0  | 2772 | 1.1889          | 0.8483   | 0.9512 | 0.8190    | 0.8802 |
| 0.0036        | 13.0  | 3003 | 1.1781          | 0.8524   | 0.9592 | 0.8196    | 0.8839 |
| 0.0036        | 14.0  | 3234 | 1.1979          | 0.8489   | 0.9572 | 0.8165    | 0.8812 |
| 0.0036        | 15.0  | 3465 | 1.0633          | 0.8635   | 0.9373 | 0.8462    | 0.8894 |
| 0.0064        | 16.0  | 3696 | 1.0781          | 0.8629   | 0.9333 | 0.8480    | 0.8886 |
| 0.0064        | 17.0  | 3927 | 1.1728          | 0.8477   | 0.9452 | 0.8216    | 0.8791 |
| 0.0033        | 18.0  | 4158 | 1.1487          | 0.8536   | 0.9432 | 0.8300    | 0.8830 |
| 0.0033        | 19.0  | 4389 | 1.1052          | 0.8600   | 0.9482 | 0.8351    | 0.8881 |
| 0.0031        | 20.0  | 4620 | 1.1933          | 0.8629   | 0.9612 | 0.8312    | 0.8915 |
| 0.0031        | 21.0  | 4851 | 1.3387          | 0.8454   | 0.9671 | 0.8071    | 0.8799 |
| 0.0029        | 22.0  | 5082 | 1.1393          | 0.8635   | 0.9482 | 0.8395    | 0.8906 |
| 0.0029        | 23.0  | 5313 | 1.2048          | 0.8617   | 0.9522 | 0.8349    | 0.8897 |
| 0.0003        | 24.0  | 5544 | 1.1798          | 0.8652   | 0.9522 | 0.8393    | 0.8922 |
| 0.0003        | 25.0  | 5775 | 1.1385          | 0.8705   | 0.9412 | 0.8529    | 0.8949 |
| 0.0014        | 26.0  | 6006 | 1.2903          | 0.8565   | 0.9532 | 0.8279    | 0.8861 |
| 0.0014        | 27.0  | 6237 | 1.1961          | 0.8635   | 0.9412 | 0.8438    | 0.8898 |
| 0.0014        | 28.0  | 6468 | 1.2178          | 0.8635   | 0.9442 | 0.8419    | 0.8901 |
| 0.0013        | 29.0  | 6699 | 1.2409          | 0.8635   | 0.9472 | 0.8401    | 0.8904 |
| 0.0013        | 30.0  | 6930 | 1.2450          | 0.8641   | 0.9482 | 0.8402    | 0.8910 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1