---
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: eurobert210m_Mobilite_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_Mobilite_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: 0.0135
- Accuracy: 0.9942
- F1: 0.9942

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.2363        | 1.0   | 124  | 0.8864          | 0.6790   | 0.6323 |
| 0.588         | 2.0   | 248  | 0.3959          | 0.8901   | 0.8796 |
| 0.3365        | 3.0   | 372  | 0.1947          | 0.9506   | 0.9502 |
| 0.2177        | 4.0   | 496  | 0.1856          | 0.9549   | 0.9540 |
| 0.1708        | 5.0   | 620  | 0.1072          | 0.9786   | 0.9786 |
| 0.1455        | 6.0   | 744  | 0.1288          | 0.9713   | 0.9716 |
| 0.1217        | 7.0   | 868  | 0.0800          | 0.9836   | 0.9837 |
| 0.0986        | 8.0   | 992  | 0.0599          | 0.9874   | 0.9874 |
| 0.0735        | 9.0   | 1116 | 0.0480          | 0.9892   | 0.9892 |
| 0.0577        | 10.0  | 1240 | 0.0305          | 0.9922   | 0.9922 |
| 0.0619        | 11.0  | 1364 | 0.0475          | 0.9897   | 0.9897 |
| 0.0449        | 12.0  | 1488 | 0.0991          | 0.9816   | 0.9814 |
| 0.0566        | 13.0  | 1612 | 0.0215          | 0.9932   | 0.9932 |
| 0.0473        | 14.0  | 1736 | 0.0228          | 0.9939   | 0.9939 |
| 0.0344        | 15.0  | 1860 | 0.0336          | 0.9922   | 0.9922 |
| 0.04          | 16.0  | 1984 | 0.0426          | 0.9909   | 0.9909 |
| 0.0353        | 17.0  | 2108 | 0.0191          | 0.9945   | 0.9945 |
| 0.0448        | 18.0  | 2232 | 0.0193          | 0.9932   | 0.9932 |
| 0.0359        | 19.0  | 2356 | 0.0184          | 0.9942   | 0.9942 |
| 0.0314        | 20.0  | 2480 | 0.0146          | 0.9942   | 0.9942 |
| 0.0257        | 21.0  | 2604 | 0.0173          | 0.9942   | 0.9942 |
| 0.0208        | 22.0  | 2728 | 0.0144          | 0.9942   | 0.9942 |
| 0.0334        | 23.0  | 2852 | 0.0135          | 0.9942   | 0.9942 |


### Framework versions

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