---
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-610m
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: EuroBERT-immigration-binary-german
  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. -->

# EuroBERT-immigration-binary-german

This model is a fine-tuned version of [EuroBERT/EuroBERT-610m](https://huggingface.co/EuroBERT/EuroBERT-610m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6248
- Accuracy: 0.9087
- F1 Macro: 0.9065
- Accuracy Balanced: 0.9061
- F1 Micro: 0.9087
- Precision Macro: 0.9070
- Recall Macro: 0.9061
- Precision Micro: 0.9087
- Recall Micro: 0.9087

## 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: 4
- eval_batch_size: 40
- 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
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.5811        | 1.0   | 1578 | 0.5772          | 0.8834   | 0.8755   | 0.8650            | 0.8834   | 0.9083          | 0.8650       | 0.8834          | 0.8834       |
| 0.3917        | 2.0   | 3156 | 0.4164          | 0.8992   | 0.8956   | 0.8912            | 0.8992   | 0.9027          | 0.8912       | 0.8992          | 0.8992       |
| 0.3085        | 3.0   | 4734 | 0.4480          | 0.9144   | 0.9122   | 0.9106            | 0.9144   | 0.9139          | 0.9106       | 0.9144          | 0.9144       |
| 0.1768        | 4.0   | 6312 | 0.6187          | 0.9056   | 0.9021   | 0.8973            | 0.9056   | 0.9100          | 0.8973       | 0.9056          | 0.9056       |
| 0.0676        | 5.0   | 7890 | 0.6248          | 0.9087   | 0.9065   | 0.9061            | 0.9087   | 0.9070          | 0.9061       | 0.9087          | 0.9087       |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1