---
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: eurobert210m_EconomieCirculaire_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_EconomieCirculaire_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: 0.0142
- Accuracy: 0.9978
- F1: 0.9978

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6621        | 1.0   | 98   | 0.2769          | 0.9096   | 0.9112 |
| 0.296         | 2.0   | 196  | 0.1087          | 0.9671   | 0.9671 |
| 0.1875        | 3.0   | 294  | 0.1938          | 0.9457   | 0.9457 |
| 0.1906        | 4.0   | 392  | 0.0815          | 0.9751   | 0.9751 |
| 0.1295        | 5.0   | 490  | 0.1025          | 0.9687   | 0.9688 |
| 0.1131        | 6.0   | 588  | 0.1083          | 0.9729   | 0.9727 |
| 0.0841        | 7.0   | 686  | 0.0665          | 0.9824   | 0.9825 |
| 0.0708        | 8.0   | 784  | 0.0390          | 0.9882   | 0.9882 |
| 0.0812        | 9.0   | 882  | 0.0457          | 0.9895   | 0.9895 |
| 0.0939        | 10.0  | 980  | 0.0423          | 0.9904   | 0.9904 |
| 0.0609        | 11.0  | 1078 | 0.0196          | 0.9968   | 0.9968 |
| 0.0299        | 12.0  | 1176 | 0.0372          | 0.9939   | 0.9939 |
| 0.0192        | 13.0  | 1274 | 0.0203          | 0.9968   | 0.9968 |
| 0.0267        | 14.0  | 1372 | 0.0201          | 0.9968   | 0.9968 |
| 0.026         | 15.0  | 1470 | 0.0174          | 0.9958   | 0.9958 |
| 0.0178        | 16.0  | 1568 | 0.0349          | 0.9965   | 0.9965 |
| 0.0225        | 17.0  | 1666 | 0.0182          | 0.9971   | 0.9971 |
| 0.0381        | 18.0  | 1764 | 0.0080          | 0.9974   | 0.9974 |
| 0.0086        | 19.0  | 1862 | 0.0106          | 0.9981   | 0.9981 |
| 0.056         | 20.0  | 1960 | 0.0237          | 0.9949   | 0.9949 |
| 0.0284        | 21.0  | 2058 | 0.0142          | 0.9978   | 0.9978 |


### Framework versions

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