---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ai-browsing-categories-text
  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. -->

# ai-browsing-categories-text

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: 0.0274
- Accuracy: 0.9924
- F1: 0.9677
- Precision: 0.9737
- Recall: 0.9617

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1732        | 1.0   | 532  | 0.0586          | 0.9835   | 0.9274 | 0.9631    | 0.8943 |
| 0.0447        | 2.0   | 1064 | 0.0371          | 0.9884   | 0.9500 | 0.9681    | 0.9326 |
| 0.0272        | 3.0   | 1596 | 0.0319          | 0.9903   | 0.9583 | 0.9729    | 0.9442 |
| 0.0192        | 4.0   | 2128 | 0.0297          | 0.9907   | 0.9603 | 0.9714    | 0.9493 |
| 0.015         | 5.0   | 2660 | 0.0283          | 0.9917   | 0.9646 | 0.9736    | 0.9557 |
| 0.0115        | 6.0   | 3192 | 0.0284          | 0.9921   | 0.9662 | 0.9752    | 0.9573 |
| 0.0099        | 7.0   | 3724 | 0.0274          | 0.9927   | 0.9689 | 0.9761    | 0.9617 |
| 0.0079        | 8.0   | 4256 | 0.0274          | 0.9924   | 0.9677 | 0.9737    | 0.9617 |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4-dev.0