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End of training

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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: eurobert_Eau
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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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+ # eurobert_Eau
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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: 0.1286
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+ - Accuracy: 0.9508
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+ - F1: 0.9491
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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: 30
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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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+ | 0.8035 | 1.0 | 67 | 0.4268 | 0.8809 | 0.8836 |
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+ | 0.3476 | 2.0 | 134 | 0.2320 | 0.9168 | 0.9174 |
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+ | 0.263 | 3.0 | 201 | 0.2839 | 0.9031 | 0.9010 |
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+ | 0.2119 | 4.0 | 268 | 0.1522 | 0.9385 | 0.9393 |
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+ | 0.191 | 5.0 | 335 | 0.1765 | 0.9314 | 0.9296 |
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+ | 0.1797 | 6.0 | 402 | 0.1228 | 0.9480 | 0.9474 |
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+ | 0.1639 | 7.0 | 469 | 0.1065 | 0.9485 | 0.9500 |
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+ | 0.1422 | 8.0 | 536 | 0.1347 | 0.9428 | 0.9423 |
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+ | 0.1237 | 9.0 | 603 | 0.1047 | 0.9504 | 0.9510 |
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+ | 0.1119 | 10.0 | 670 | 0.1286 | 0.9508 | 0.9491 |
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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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