---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-classifier
  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-classifier

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: 0.2565
- Accuracy: 0.8991
- F1: 0.8045

## 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: 32
- eval_batch_size: 32
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0      | 0    | 0.7631          | 0.2536   | 0.4046 |
| No log        | 0.2020 | 79   | 0.3566          | 0.8559   | 0.6689 |
| No log        | 0.4041 | 158  | 0.3387          | 0.8573   | 0.7506 |
| No log        | 0.6061 | 237  | 0.2934          | 0.8804   | 0.7688 |
| No log        | 0.8082 | 316  | 0.2863          | 0.8890   | 0.7947 |
| No log        | 1.0102 | 395  | 0.2716          | 0.8876   | 0.7869 |
| No log        | 1.2123 | 474  | 0.2799          | 0.8905   | 0.7877 |
| 0.3458        | 1.4143 | 553  | 0.2581          | 0.8977   | 0.8033 |
| 0.3458        | 1.6164 | 632  | 0.2539          | 0.8977   | 0.8011 |
| 0.3458        | 1.8184 | 711  | 0.2565          | 0.8991   | 0.8045 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1