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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: EuroBERT/EuroBERT-210m |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: eurobert210m_Energie_v1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# eurobert210m_Energie_v1 |
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This model is a fine-tuned version of [EuroBERT/EuroBERT-210m](https://huggingface.co/EuroBERT/EuroBERT-210m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0418 |
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- Accuracy: 0.9900 |
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- F1: 0.9900 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.4438 | 1.0 | 116 | 0.9257 | 0.6453 | 0.5924 | |
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| 0.7711 | 2.0 | 232 | 0.5221 | 0.8263 | 0.8141 | |
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| 0.3803 | 3.0 | 348 | 0.1986 | 0.9357 | 0.9330 | |
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| 0.2678 | 4.0 | 464 | 0.1487 | 0.9501 | 0.9508 | |
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| 0.1839 | 5.0 | 580 | 0.1222 | 0.9642 | 0.9642 | |
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| 0.1736 | 6.0 | 696 | 0.1348 | 0.9634 | 0.9638 | |
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| 0.1207 | 7.0 | 812 | 0.0549 | 0.9829 | 0.9828 | |
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| 0.1022 | 8.0 | 928 | 0.0642 | 0.9802 | 0.9804 | |
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| 0.0699 | 9.0 | 1044 | 0.0723 | 0.9777 | 0.9773 | |
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| 0.0584 | 10.0 | 1160 | 0.0315 | 0.9886 | 0.9886 | |
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| 0.0617 | 11.0 | 1276 | 0.0506 | 0.9862 | 0.9861 | |
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| 0.0591 | 12.0 | 1392 | 0.0445 | 0.9867 | 0.9867 | |
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| 0.0599 | 13.0 | 1508 | 0.0402 | 0.9870 | 0.9870 | |
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| 0.0595 | 14.0 | 1624 | 0.0952 | 0.9788 | 0.9791 | |
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| 0.0401 | 15.0 | 1740 | 0.0526 | 0.9853 | 0.9854 | |
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| 0.0424 | 16.0 | 1856 | 0.0305 | 0.9902 | 0.9902 | |
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| 0.0323 | 17.0 | 1972 | 0.0969 | 0.9802 | 0.9798 | |
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| 0.0664 | 18.0 | 2088 | 0.0359 | 0.9881 | 0.9879 | |
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| 0.031 | 19.0 | 2204 | 0.0372 | 0.9897 | 0.9897 | |
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| 0.0239 | 20.0 | 2320 | 0.0418 | 0.9900 | 0.9900 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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