---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-german-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: trainer_output
  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. -->

# trainer_output

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: 0.3713
- Accuracy: 0.8983
- F1: 0.8950

## 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 | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.7353        | 0.9881 | 750  | 0.4152          | 0.8782   | 0.8693 |
| 0.3605        | 1.9763 | 1500 | 0.3601          | 0.8978   | 0.8947 |
| 0.2648        | 2.9644 | 2250 | 0.3713          | 0.8983   | 0.8950 |


### Framework versions

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