---
library_name: transformers
base_model: FacebookAI/xlm-roberta-large-finetuned-conll03-german
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_model
  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_model

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large-finetuned-conll03-german](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-german) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4387
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9150

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 4    | 0.5376          | 0.0       | 0.0    | 0.0 | 0.9169   |
| No log        | 2.0   | 8    | 0.4387          | 0.0       | 0.0    | 0.0 | 0.9150   |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.2