---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: germanic_antielite_Dutch
  results: []
---

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

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2547
- Accuracy: 0.8557
- F1: 0.0667

## 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 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 97   | 0.6825          | 0.8376   | 0.1127 |
| 0.1766        | 2.0   | 194  | 0.4794          | 0.8428   | 0.0896 |
| 0.2952        | 3.0   | 291  | 0.8158          | 0.8299   | 0.1081 |
| 0.1576        | 4.0   | 388  | 0.9771          | 0.8531   | 0.0952 |
| 0.0718        | 5.0   | 485  | 1.1854          | 0.8247   | 0.0811 |
| 0.0352        | 6.0   | 582  | 1.1599          | 0.8325   | 0.0580 |
| 0.0167        | 7.0   | 679  | 1.2373          | 0.8376   | 0.0308 |
| 0.0058        | 8.0   | 776  | 1.4320          | 0.8015   | 0.0941 |
| 0.0065        | 9.0   | 873  | 1.2486          | 0.8557   | 0.0667 |
| 0.0021        | 10.0  | 970  | 1.2547          | 0.8557   | 0.0667 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3