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Ludo33
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eurobert210m_EconomieCirculaire_v1

Text Classification
Transformers
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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_EconomieCirculaire_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_EconomieCirculaire_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: 0.0142
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+ - Accuracy: 0.9978
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+ - F1: 0.9978
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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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+ | 0.6621 | 1.0 | 98 | 0.2769 | 0.9096 | 0.9112 |
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+ | 0.296 | 2.0 | 196 | 0.1087 | 0.9671 | 0.9671 |
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+ | 0.1875 | 3.0 | 294 | 0.1938 | 0.9457 | 0.9457 |
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+ | 0.1906 | 4.0 | 392 | 0.0815 | 0.9751 | 0.9751 |
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+ | 0.1295 | 5.0 | 490 | 0.1025 | 0.9687 | 0.9688 |
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+ | 0.1131 | 6.0 | 588 | 0.1083 | 0.9729 | 0.9727 |
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+ | 0.0841 | 7.0 | 686 | 0.0665 | 0.9824 | 0.9825 |
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+ | 0.0708 | 8.0 | 784 | 0.0390 | 0.9882 | 0.9882 |
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+ | 0.0812 | 9.0 | 882 | 0.0457 | 0.9895 | 0.9895 |
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+ | 0.0939 | 10.0 | 980 | 0.0423 | 0.9904 | 0.9904 |
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+ | 0.0609 | 11.0 | 1078 | 0.0196 | 0.9968 | 0.9968 |
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+ | 0.0299 | 12.0 | 1176 | 0.0372 | 0.9939 | 0.9939 |
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+ | 0.0192 | 13.0 | 1274 | 0.0203 | 0.9968 | 0.9968 |
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+ | 0.0267 | 14.0 | 1372 | 0.0201 | 0.9968 | 0.9968 |
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+ | 0.026 | 15.0 | 1470 | 0.0174 | 0.9958 | 0.9958 |
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+ | 0.0178 | 16.0 | 1568 | 0.0349 | 0.9965 | 0.9965 |
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+ | 0.0225 | 17.0 | 1666 | 0.0182 | 0.9971 | 0.9971 |
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+ | 0.0381 | 18.0 | 1764 | 0.0080 | 0.9974 | 0.9974 |
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+ | 0.0086 | 19.0 | 1862 | 0.0106 | 0.9981 | 0.9981 |
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+ | 0.056 | 20.0 | 1960 | 0.0237 | 0.9949 | 0.9949 |
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+ | 0.0284 | 21.0 | 2058 | 0.0142 | 0.9978 | 0.9978 |
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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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