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Ludo33
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eurobert210m_Mobilite_v1

Text Classification
Transformers
Safetensors
eurobert
Generated from Trainer
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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_Mobilite_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_Mobilite_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: 0.0135
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+ - Accuracy: 0.9942
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+ - F1: 0.9942
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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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+ | 1.2363 | 1.0 | 124 | 0.8864 | 0.6790 | 0.6323 |
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+ | 0.588 | 2.0 | 248 | 0.3959 | 0.8901 | 0.8796 |
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+ | 0.3365 | 3.0 | 372 | 0.1947 | 0.9506 | 0.9502 |
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+ | 0.2177 | 4.0 | 496 | 0.1856 | 0.9549 | 0.9540 |
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+ | 0.1708 | 5.0 | 620 | 0.1072 | 0.9786 | 0.9786 |
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+ | 0.1455 | 6.0 | 744 | 0.1288 | 0.9713 | 0.9716 |
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+ | 0.1217 | 7.0 | 868 | 0.0800 | 0.9836 | 0.9837 |
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+ | 0.0986 | 8.0 | 992 | 0.0599 | 0.9874 | 0.9874 |
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+ | 0.0735 | 9.0 | 1116 | 0.0480 | 0.9892 | 0.9892 |
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+ | 0.0577 | 10.0 | 1240 | 0.0305 | 0.9922 | 0.9922 |
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+ | 0.0619 | 11.0 | 1364 | 0.0475 | 0.9897 | 0.9897 |
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+ | 0.0449 | 12.0 | 1488 | 0.0991 | 0.9816 | 0.9814 |
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+ | 0.0566 | 13.0 | 1612 | 0.0215 | 0.9932 | 0.9932 |
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+ | 0.0473 | 14.0 | 1736 | 0.0228 | 0.9939 | 0.9939 |
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+ | 0.0344 | 15.0 | 1860 | 0.0336 | 0.9922 | 0.9922 |
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+ | 0.04 | 16.0 | 1984 | 0.0426 | 0.9909 | 0.9909 |
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+ | 0.0353 | 17.0 | 2108 | 0.0191 | 0.9945 | 0.9945 |
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+ | 0.0448 | 18.0 | 2232 | 0.0193 | 0.9932 | 0.9932 |
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+ | 0.0359 | 19.0 | 2356 | 0.0184 | 0.9942 | 0.9942 |
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+ | 0.0314 | 20.0 | 2480 | 0.0146 | 0.9942 | 0.9942 |
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+ | 0.0257 | 21.0 | 2604 | 0.0173 | 0.9942 | 0.9942 |
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+ | 0.0208 | 22.0 | 2728 | 0.0144 | 0.9942 | 0.9942 |
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+ | 0.0334 | 23.0 | 2852 | 0.0135 | 0.9942 | 0.9942 |
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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