---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-german-cased-own-data-ner
  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. -->

# bert-base-german-cased-own-data-ner

This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0535
- Precision: 0.7134
- Recall: 0.8536
- F1: 0.7772
- Accuracy: 0.9895

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.8   | 32   | 0.0308          | 0.7593    | 0.8    | 0.7791 | 0.9917   |
| No log        | 1.6   | 64   | 0.0342          | 0.7756    | 0.8393 | 0.8062 | 0.9911   |
| No log        | 2.4   | 96   | 0.0457          | 0.7764    | 0.8679 | 0.8196 | 0.9906   |
| No log        | 3.2   | 128  | 0.0383          | 0.7524    | 0.8464 | 0.7966 | 0.9911   |
| No log        | 4.0   | 160  | 0.0420          | 0.7539    | 0.8536 | 0.8007 | 0.9907   |
| No log        | 4.8   | 192  | 0.0535          | 0.7134    | 0.8536 | 0.7772 | 0.9895   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.9.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1