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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
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