---
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: eurobert210m_RSE_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_RSE_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: 0.0069
- Accuracy: 0.9982
- F1: 0.9982

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7448        | 1.0   | 138  | 0.2380          | 0.9194   | 0.9200 |
| 0.3157        | 2.0   | 276  | 0.1846          | 0.9421   | 0.9419 |
| 0.2241        | 3.0   | 414  | 0.1905          | 0.9373   | 0.9371 |
| 0.1923        | 4.0   | 552  | 0.0821          | 0.9739   | 0.9739 |
| 0.1312        | 5.0   | 690  | 0.1449          | 0.9614   | 0.9616 |
| 0.1418        | 6.0   | 828  | 0.0782          | 0.9796   | 0.9795 |
| 0.1008        | 7.0   | 966  | 0.0579          | 0.9877   | 0.9877 |
| 0.0981        | 8.0   | 1104 | 0.0363          | 0.9893   | 0.9893 |
| 0.0723        | 9.0   | 1242 | 0.1002          | 0.9789   | 0.9789 |
| 0.0846        | 10.0  | 1380 | 0.0457          | 0.9907   | 0.9907 |
| 0.0779        | 11.0  | 1518 | 0.0620          | 0.9880   | 0.9880 |
| 0.0676        | 12.0  | 1656 | 0.0314          | 0.9932   | 0.9932 |
| 0.0389        | 13.0  | 1794 | 0.0232          | 0.9950   | 0.9950 |
| 0.0453        | 14.0  | 1932 | 0.0145          | 0.9966   | 0.9966 |
| 0.0328        | 15.0  | 2070 | 0.0303          | 0.9936   | 0.9936 |
| 0.0316        | 16.0  | 2208 | 0.0247          | 0.9948   | 0.9948 |
| 0.0191        | 17.0  | 2346 | 0.0070          | 0.9984   | 0.9984 |
| 0.0209        | 18.0  | 2484 | 0.0069          | 0.9982   | 0.9982 |


### Framework versions

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