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---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_analyse_visage_classifier-only_fr_lr1e-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# camembert_ccnet_classification_analyse_visage_classifier-only_fr_lr1e-3
This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co./camembert/camembert-base-ccnet) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0117
- Accuracy: 1.0
- Learning Rate: 0.0
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9997 | 1.0 | 4 | 0.6869 | 0.8333 | 0.0010 |
| 0.6989 | 2.0 | 8 | 0.4634 | 1.0 | 0.0009 |
| 0.4979 | 3.0 | 12 | 0.3029 | 1.0 | 0.0009 |
| 0.3335 | 4.0 | 16 | 0.2251 | 1.0 | 0.0009 |
| 0.2709 | 5.0 | 20 | 0.1619 | 1.0 | 0.0008 |
| 0.2246 | 6.0 | 24 | 0.1013 | 1.0 | 0.0008 |
| 0.1836 | 7.0 | 28 | 0.0968 | 1.0 | 0.0008 |
| 0.1711 | 8.0 | 32 | 0.0767 | 1.0 | 0.0007 |
| 0.2015 | 9.0 | 36 | 0.0548 | 1.0 | 0.0007 |
| 0.1353 | 10.0 | 40 | 0.0463 | 1.0 | 0.0007 |
| 0.081 | 11.0 | 44 | 0.0307 | 1.0 | 0.0006 |
| 0.1331 | 12.0 | 48 | 0.0519 | 1.0 | 0.0006 |
| 0.11 | 13.0 | 52 | 0.0393 | 1.0 | 0.0006 |
| 0.0737 | 14.0 | 56 | 0.0289 | 1.0 | 0.0005 |
| 0.0627 | 15.0 | 60 | 0.0251 | 1.0 | 0.0005 |
| 0.0477 | 16.0 | 64 | 0.0174 | 1.0 | 0.0005 |
| 0.0564 | 17.0 | 68 | 0.0155 | 1.0 | 0.0004 |
| 0.054 | 18.0 | 72 | 0.0128 | 1.0 | 0.0004 |
| 0.0486 | 19.0 | 76 | 0.0154 | 1.0 | 0.0004 |
| 0.0444 | 20.0 | 80 | 0.0122 | 1.0 | 0.0003 |
| 0.0394 | 21.0 | 84 | 0.0166 | 1.0 | 0.0003 |
| 0.0522 | 22.0 | 88 | 0.0146 | 1.0 | 0.0003 |
| 0.0416 | 23.0 | 92 | 0.0092 | 1.0 | 0.0002 |
| 0.0553 | 24.0 | 96 | 0.0074 | 1.0 | 0.0002 |
| 0.0791 | 25.0 | 100 | 0.0074 | 1.0 | 0.0002 |
| 0.0798 | 26.0 | 104 | 0.0083 | 1.0 | 0.0001 |
| 0.0412 | 27.0 | 108 | 0.0107 | 1.0 | 0.0001 |
| 0.0406 | 28.0 | 112 | 0.0127 | 1.0 | 0.0001 |
| 0.0407 | 29.0 | 116 | 0.0123 | 1.0 | 0.0000 |
| 0.0534 | 30.0 | 120 | 0.0117 | 1.0 | 0.0 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
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