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

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: 0.1286
- Accuracy: 0.9508
- F1: 0.9491

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8035        | 1.0   | 67   | 0.4268          | 0.8809   | 0.8836 |
| 0.3476        | 2.0   | 134  | 0.2320          | 0.9168   | 0.9174 |
| 0.263         | 3.0   | 201  | 0.2839          | 0.9031   | 0.9010 |
| 0.2119        | 4.0   | 268  | 0.1522          | 0.9385   | 0.9393 |
| 0.191         | 5.0   | 335  | 0.1765          | 0.9314   | 0.9296 |
| 0.1797        | 6.0   | 402  | 0.1228          | 0.9480   | 0.9474 |
| 0.1639        | 7.0   | 469  | 0.1065          | 0.9485   | 0.9500 |
| 0.1422        | 8.0   | 536  | 0.1347          | 0.9428   | 0.9423 |
| 0.1237        | 9.0   | 603  | 0.1047          | 0.9504   | 0.9510 |
| 0.1119        | 10.0  | 670  | 0.1286          | 0.9508   | 0.9491 |


### Framework versions

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