---
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