---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-german-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: flausch_span_distilbert-base-german-cased_non_labeled_spans
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# flausch_span_distilbert-base-german-cased_non_labeled_spans

This model is a fine-tuned version of [distilbert/distilbert-base-german-cased](https://huggingface.co/distilbert/distilbert-base-german-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2139
- Model Preparation Time: 0.0025
- Precision: 0.5524
- Recall: 0.6267
- F1: 0.5872

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:---------:|:------:|:------:|
| 0.3169        | 0.4233 | 750  | 0.2247          | 0.0025                 | 0.3873    | 0.4623 | 0.4215 |
| 0.2218        | 0.8465 | 1500 | 0.2164          | 0.0025                 | 0.4657    | 0.5182 | 0.4906 |
| 0.1831        | 1.2698 | 2250 | 0.2090          | 0.0025                 | 0.4974    | 0.5964 | 0.5424 |
| 0.1564        | 1.6930 | 3000 | 0.2038          | 0.0025                 | 0.5212    | 0.6172 | 0.5652 |
| 0.1535        | 2.1163 | 3750 | 0.2118          | 0.0025                 | 0.5447    | 0.6087 | 0.5749 |
| 0.1206        | 2.5395 | 4500 | 0.2106          | 0.0025                 | 0.5418    | 0.6262 | 0.5810 |
| 0.1182        | 2.9628 | 5250 | 0.2139          | 0.0025                 | 0.5524    | 0.6267 | 0.5872 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1