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--- |
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base_model: camembert/camembert-base-ccnet |
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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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model-index: |
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- name: camembert_ccnet_classification_analyse_visage_classifier-only_fr_lr1e-3 |
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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_ccnet_classification_analyse_visage_classifier-only_fr_lr1e-3 |
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This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co./camembert/camembert-base-ccnet) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0117 |
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- Accuracy: 1.0 |
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- Learning Rate: 0.0 |
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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: 0.001 |
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- train_batch_size: 24 |
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- eval_batch_size: 192 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.9997 | 1.0 | 4 | 0.6869 | 0.8333 | 0.0010 | |
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| 0.6989 | 2.0 | 8 | 0.4634 | 1.0 | 0.0009 | |
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| 0.4979 | 3.0 | 12 | 0.3029 | 1.0 | 0.0009 | |
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| 0.3335 | 4.0 | 16 | 0.2251 | 1.0 | 0.0009 | |
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| 0.2709 | 5.0 | 20 | 0.1619 | 1.0 | 0.0008 | |
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| 0.2246 | 6.0 | 24 | 0.1013 | 1.0 | 0.0008 | |
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| 0.1836 | 7.0 | 28 | 0.0968 | 1.0 | 0.0008 | |
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| 0.1711 | 8.0 | 32 | 0.0767 | 1.0 | 0.0007 | |
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| 0.2015 | 9.0 | 36 | 0.0548 | 1.0 | 0.0007 | |
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| 0.1353 | 10.0 | 40 | 0.0463 | 1.0 | 0.0007 | |
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| 0.081 | 11.0 | 44 | 0.0307 | 1.0 | 0.0006 | |
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| 0.1331 | 12.0 | 48 | 0.0519 | 1.0 | 0.0006 | |
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| 0.11 | 13.0 | 52 | 0.0393 | 1.0 | 0.0006 | |
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| 0.0737 | 14.0 | 56 | 0.0289 | 1.0 | 0.0005 | |
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| 0.0627 | 15.0 | 60 | 0.0251 | 1.0 | 0.0005 | |
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| 0.0477 | 16.0 | 64 | 0.0174 | 1.0 | 0.0005 | |
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| 0.0564 | 17.0 | 68 | 0.0155 | 1.0 | 0.0004 | |
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| 0.054 | 18.0 | 72 | 0.0128 | 1.0 | 0.0004 | |
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| 0.0486 | 19.0 | 76 | 0.0154 | 1.0 | 0.0004 | |
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| 0.0444 | 20.0 | 80 | 0.0122 | 1.0 | 0.0003 | |
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| 0.0394 | 21.0 | 84 | 0.0166 | 1.0 | 0.0003 | |
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| 0.0522 | 22.0 | 88 | 0.0146 | 1.0 | 0.0003 | |
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| 0.0416 | 23.0 | 92 | 0.0092 | 1.0 | 0.0002 | |
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| 0.0553 | 24.0 | 96 | 0.0074 | 1.0 | 0.0002 | |
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| 0.0791 | 25.0 | 100 | 0.0074 | 1.0 | 0.0002 | |
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| 0.0798 | 26.0 | 104 | 0.0083 | 1.0 | 0.0001 | |
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| 0.0412 | 27.0 | 108 | 0.0107 | 1.0 | 0.0001 | |
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| 0.0406 | 28.0 | 112 | 0.0127 | 1.0 | 0.0001 | |
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| 0.0407 | 29.0 | 116 | 0.0123 | 1.0 | 0.0000 | |
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| 0.0534 | 30.0 | 120 | 0.0117 | 1.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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