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eurobert210m_Energie_v1

Text Classification
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eurobert
Generated from Trainer
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README.md ADDED
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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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+
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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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+
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+ # eurobert210m_Energie_v1
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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