---
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: camembert-base-finetuned-sentence-simplification-fr
  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-base-finetuned-sentence-simplification-fr

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0225
- Rouge1: 98.9126
- Rouge2: 96.9479
- Rougel: 97.9209
- Rougelsum: 98.9061

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.2555        | 1.0   | 375  | 0.7613          | 41.6446 | 20.4343 | 38.0279 | 41.5954   |
| 0.679         | 2.0   | 750  | 0.3463          | 72.8071 | 48.9808 | 60.7026 | 72.8052   |
| 0.4088        | 3.0   | 1125 | 0.1948          | 85.3976 | 65.3267 | 74.3572 | 85.3705   |
| 0.2795        | 4.0   | 1500 | 0.1098          | 91.8037 | 78.9948 | 85.9716 | 91.8695   |
| 0.204         | 5.0   | 1875 | 0.0776          | 94.6475 | 84.3954 | 89.9382 | 94.6349   |
| 0.1544        | 6.0   | 2250 | 0.0454          | 97.197  | 91.932  | 94.8966 | 97.1919   |
| 0.1212        | 7.0   | 2625 | 0.0384          | 97.5777 | 93.2443 | 95.4839 | 97.5692   |
| 0.1037        | 8.0   | 3000 | 0.0315          | 97.8918 | 95.2195 | 96.8449 | 97.9063   |
| 0.0942        | 9.0   | 3375 | 0.0253          | 98.6234 | 96.5271 | 97.6489 | 98.6284   |
| 0.0823        | 10.0  | 3750 | 0.0225          | 98.9126 | 96.9479 | 97.9209 | 98.9061   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1