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---
library_name: transformers
license: mit
base_model: almanach/camembert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: td2
results: []
language:
- fr
---
<!-- 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. -->
# td2
TD2 - ESGI
# Ahmed Ennaifer & Sarra Chabane Chaouche
This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on the None dataset.
It achieves the following results on the evaluation set of train/test:
- Loss: 0.0128
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9983
# The model got an accuracy of `0.998` on the seperate eval dataset : `test_fr`
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log | 1.0 | 160 | 0.0455 | 0.0 | 0.0 | 0.0 | 0.9975 |
| No log | 2.0 | 320 | 0.0292 | 0.0 | 0.0 | 0.0 | 0.9981 |
| No log | 3.0 | 480 | 0.0224 | 0.0 | 0.0 | 0.0 | 0.9981 |
| 0.0837 | 4.0 | 640 | 0.0188 | 0.0 | 0.0 | 0.0 | 0.9981 |
| 0.0837 | 5.0 | 800 | 0.0166 | 0.0 | 0.0 | 0.0 | 0.9979 |
| 0.0837 | 6.0 | 960 | 0.0148 | 0.0 | 0.0 | 0.0 | 0.9981 |
| 0.0182 | 7.0 | 1120 | 0.0139 | 0.0 | 0.0 | 0.0 | 0.9982 |
| 0.0182 | 8.0 | 1280 | 0.0133 | 0.0 | 0.0 | 0.0 | 0.9981 |
| 0.0182 | 9.0 | 1440 | 0.0129 | 0.0 | 0.0 | 0.0 | 0.9982 |
| 0.0122 | 10.0 | 1600 | 0.0128 | 0.0 | 0.0 | 0.0 | 0.9983 |
### Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1 |