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README.md
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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_Eau_v2
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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_Eau_v2
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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: 0.0680
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- Accuracy: 0.9584
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- F1: 0.9595
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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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| 1.4372 | 1.0 | 67 | 0.9689 | 0.6322 | 0.5664 |
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| 0.8205 | 2.0 | 134 | 0.6235 | 0.8213 | 0.8222 |
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| 0.4899 | 3.0 | 201 | 0.4782 | 0.8326 | 0.8367 |
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| 0.3598 | 4.0 | 268 | 0.2252 | 0.9196 | 0.9200 |
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| 0.2854 | 5.0 | 335 | 0.2137 | 0.9258 | 0.9265 |
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| 0.2054 | 6.0 | 402 | 0.1284 | 0.9452 | 0.9443 |
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| 0.1735 | 7.0 | 469 | 0.1984 | 0.9296 | 0.9303 |
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| 0.1763 | 8.0 | 536 | 0.1177 | 0.9409 | 0.9379 |
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| 0.1601 | 9.0 | 603 | 0.1133 | 0.9485 | 0.9462 |
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| 0.1206 | 10.0 | 670 | 0.1219 | 0.9461 | 0.9448 |
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| 0.1269 | 11.0 | 737 | 0.0756 | 0.9565 | 0.9575 |
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| 0.1238 | 12.0 | 804 | 0.1025 | 0.9522 | 0.9539 |
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| 0.0969 | 13.0 | 871 | 0.0823 | 0.9570 | 0.9580 |
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| 0.1046 | 14.0 | 938 | 0.0802 | 0.9527 | 0.9513 |
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| 0.1101 | 15.0 | 1005 | 0.0797 | 0.9546 | 0.9539 |
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| 0.0864 | 16.0 | 1072 | 0.0853 | 0.9565 | 0.9550 |
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| 0.1002 | 17.0 | 1139 | 0.0696 | 0.9579 | 0.9582 |
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| 0.0794 | 18.0 | 1206 | 0.0774 | 0.9579 | 0.9588 |
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| 0.0849 | 19.0 | 1273 | 0.0719 | 0.9546 | 0.9529 |
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| 0.0867 | 20.0 | 1340 | 0.0723 | 0.9589 | 0.9575 |
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| 0.0952 | 21.0 | 1407 | 0.0680 | 0.9584 | 0.9595 |
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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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