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---
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
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