---
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: eurobert210m_Energie_v1
  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. -->

# eurobert210m_Energie_v1

This model is a fine-tuned version of [EuroBERT/EuroBERT-210m](https://huggingface.co/EuroBERT/EuroBERT-210m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0418
- Accuracy: 0.9900
- F1: 0.9900

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.4438        | 1.0   | 116  | 0.9257          | 0.6453   | 0.5924 |
| 0.7711        | 2.0   | 232  | 0.5221          | 0.8263   | 0.8141 |
| 0.3803        | 3.0   | 348  | 0.1986          | 0.9357   | 0.9330 |
| 0.2678        | 4.0   | 464  | 0.1487          | 0.9501   | 0.9508 |
| 0.1839        | 5.0   | 580  | 0.1222          | 0.9642   | 0.9642 |
| 0.1736        | 6.0   | 696  | 0.1348          | 0.9634   | 0.9638 |
| 0.1207        | 7.0   | 812  | 0.0549          | 0.9829   | 0.9828 |
| 0.1022        | 8.0   | 928  | 0.0642          | 0.9802   | 0.9804 |
| 0.0699        | 9.0   | 1044 | 0.0723          | 0.9777   | 0.9773 |
| 0.0584        | 10.0  | 1160 | 0.0315          | 0.9886   | 0.9886 |
| 0.0617        | 11.0  | 1276 | 0.0506          | 0.9862   | 0.9861 |
| 0.0591        | 12.0  | 1392 | 0.0445          | 0.9867   | 0.9867 |
| 0.0599        | 13.0  | 1508 | 0.0402          | 0.9870   | 0.9870 |
| 0.0595        | 14.0  | 1624 | 0.0952          | 0.9788   | 0.9791 |
| 0.0401        | 15.0  | 1740 | 0.0526          | 0.9853   | 0.9854 |
| 0.0424        | 16.0  | 1856 | 0.0305          | 0.9902   | 0.9902 |
| 0.0323        | 17.0  | 1972 | 0.0969          | 0.9802   | 0.9798 |
| 0.0664        | 18.0  | 2088 | 0.0359          | 0.9881   | 0.9879 |
| 0.031         | 19.0  | 2204 | 0.0372          | 0.9897   | 0.9897 |
| 0.0239        | 20.0  | 2320 | 0.0418          | 0.9900   | 0.9900 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0