transformers tensorboard safetensors encoder-decoder text2text-generation generated_from_trainer base_model:mrm8488/camembert2camembert_shared-finetuned-french-summarization base_model:finetune:mrm8488/camembert2camembert_shared-finetuned-french-summarization autotrain_compatible endpoints_compatible region:us
---
base_model: mrm8488/camembert2camembert_shared-finetuned-french-summarization
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: camembert2camembert_shared-finetuned-french-summarization_finetuned_12_06_14_23
  results: []
---

Ce modèle a été finetuné avec 3336 + 664 offres. (Train + Validation) Le jeu de données a été oversamplé de façon à créer une répartition des classes homogène (15 par classe environ).

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# camembert2camembert_shared-finetuned-french-summarization_finetuned_12_06_14_23

This model is a fine-tuned version of [mrm8488/camembert2camembert_shared-finetuned-french-summarization](https://huggingface.co/mrm8488/camembert2camembert_shared-finetuned-french-summarization) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2819
- Rouge1: 0.4184
- Rouge2: 0.1729
- Rougel: 0.3116
- Rougelsum: 0.3116
- Gen Len: 57.0486

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.5592        | 1.0   | 3336 | 1.2819          | 0.4184 | 0.1729 | 0.3116 | 0.3116    | 57.0486 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
