---
license: mit
base_model: bert-base-german-dbmdz-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: product_classifier_split_url_nodigit_all
  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. -->

# product_classifier_split_url_nodigit_all

This model is a fine-tuned version of [bert-base-german-dbmdz-uncased](https://huggingface.co/bert-base-german-dbmdz-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1833
- Accuracy: 0.9734
- F1: 0.9732
- Precision: 0.9731
- Recall: 0.9734

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0385        | 1.0   | 1300 | 0.1880          | 0.9666   | 0.9663 | 0.9665    | 0.9666 |
| 0.0198        | 2.0   | 2600 | 0.1707          | 0.9718   | 0.9718 | 0.9719    | 0.9718 |
| 0.0083        | 3.0   | 3900 | 0.1833          | 0.9734   | 0.9732 | 0.9731    | 0.9734 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3