---
license: mit
base_model: google-bert/bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: gBERT_sa_cv_9_fold4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gBERT_sa_cv_9_fold4

This model is a fine-tuned version of [google-bert/bert-base-german-cased](https://huggingface.co/google-bert/bert-base-german-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6577
- F1: 0.6905

## 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: 4.47e-05
- train_batch_size: 16
- eval_batch_size: 32
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 325  | 0.4453          | 0.5414 |
| 0.4336        | 2.0   | 650  | 0.5178          | 0.6659 |
| 0.4336        | 3.0   | 975  | 0.6577          | 0.6905 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1