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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: camembert-base-articles-ner-backup |
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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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# camembert-base-articles-ner-backup |
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This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6701 |
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- F1: 0.8723 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.9205 | 1.0 | 6 | 1.7426 | 0.0 | |
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| 1.6476 | 2.0 | 12 | 1.5415 | 0.0 | |
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| 1.4607 | 3.0 | 18 | 1.3944 | 0.0635 | |
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| 1.3299 | 4.0 | 24 | 1.2587 | 0.4848 | |
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| 1.1973 | 5.0 | 30 | 1.1287 | 0.6207 | |
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| 1.0707 | 6.0 | 36 | 1.0110 | 0.8043 | |
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| 0.972 | 7.0 | 42 | 0.9266 | 0.8696 | |
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| 0.8877 | 8.0 | 48 | 0.8632 | 0.8602 | |
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| 0.8231 | 9.0 | 54 | 0.8279 | 0.8511 | |
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| 0.7723 | 10.0 | 60 | 0.8001 | 0.8511 | |
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| 0.7309 | 11.0 | 66 | 0.7617 | 0.8602 | |
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| 0.6902 | 12.0 | 72 | 0.7364 | 0.8602 | |
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| 0.6601 | 13.0 | 78 | 0.7104 | 0.8723 | |
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| 0.6306 | 14.0 | 84 | 0.7062 | 0.8723 | |
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| 0.6127 | 15.0 | 90 | 0.6896 | 0.8602 | |
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| 0.605 | 16.0 | 96 | 0.6743 | 0.8723 | |
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| 0.5892 | 17.0 | 102 | 0.6801 | 0.8723 | |
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| 0.5843 | 18.0 | 108 | 0.6797 | 0.8723 | |
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| 0.5731 | 19.0 | 114 | 0.6731 | 0.8723 | |
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| 0.5707 | 20.0 | 120 | 0.6701 | 0.8723 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.0 |
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- Tokenizers 0.13.2 |
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