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README.md
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---
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license: mit
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base_model: almanach/camembert-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: camenBERT
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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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# camenBERT
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This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0689
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- Precision: 0.9837
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- Recall: 0.9846
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- F1: 0.9842
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- Accuracy: 0.9849
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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: 2e-05
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- train_batch_size: 10
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- eval_batch_size: 10
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.3987 | 1.0 | 1782 | 0.2233 | 0.9743 | 0.9762 | 0.9753 | 0.9760 |
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| 0.1243 | 2.0 | 3564 | 0.1126 | 0.9772 | 0.9782 | 0.9777 | 0.9790 |
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| 0.0793 | 3.0 | 5346 | 0.0837 | 0.9794 | 0.9813 | 0.9804 | 0.9819 |
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| 0.0574 | 4.0 | 7128 | 0.0758 | 0.9816 | 0.9827 | 0.9821 | 0.9828 |
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| 0.0462 | 5.0 | 8910 | 0.0711 | 0.9830 | 0.9839 | 0.9835 | 0.9844 |
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| 0.0428 | 6.0 | 10692 | 0.0689 | 0.9837 | 0.9846 | 0.9842 | 0.9849 |
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### Framework versions
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- Transformers 4.40.0
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- Pytorch 2.2.2+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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