End of training

README.md

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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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