---
license: apache-2.0
base_model: mschiesser/ner-bert-german
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-bert-german-addresses-finetuned
  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. -->

# ner-bert-german-addresses-finetuned

This model is a fine-tuned version of [mschiesser/ner-bert-german](https://huggingface.co/mschiesser/ner-bert-german) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 64
- eval_batch_size: 64
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0006        | 1.0   | 14959 | 0.0000          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.0           | 2.0   | 29918 | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0           | 3.0   | 44877 | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.15.2