---
license: apache-2.0
base_model: moussaKam/barthez-orangesum-abstract
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: barthez-orange-ft
  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. -->

# barthez-orange-ft

This model is a fine-tuned version of [moussaKam/barthez-orangesum-abstract](https://huggingface.co/moussaKam/barthez-orangesum-abstract) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1689
- Rouge1: 0.6719
- Rouge2: 0.6536
- Rougel: 0.6719
- Rougelsum: 0.6722
- Gen Len: 20.0

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 31   | 4.6662          | 0.6719 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 1.99  | 62   | 0.6939          | 0.6718 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 2.99  | 93   | 0.2939          | 0.6718 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 3.98  | 124  | 0.2089          | 0.6719 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 4.98  | 155  | 0.1880          | 0.6719 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 5.98  | 186  | 0.1795          | 0.6719 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 6.97  | 217  | 0.1752          | 0.6719 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 8.0   | 249  | 0.1732          | 0.6719 | 0.6535 | 0.6718 | 0.6721    | 20.0    |
| No log        | 9.0   | 280  | 0.1716          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 9.99  | 311  | 0.1707          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 10.99 | 342  | 0.1704          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 11.98 | 373  | 0.1696          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 12.98 | 404  | 0.1698          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 13.98 | 435  | 0.1695          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 14.97 | 466  | 0.1693          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| No log        | 16.0  | 498  | 0.1691          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| 0.9743        | 17.0  | 529  | 0.1691          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| 0.9743        | 17.99 | 560  | 0.1690          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| 0.9743        | 18.99 | 591  | 0.1689          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |
| 0.9743        | 19.92 | 620  | 0.1689          | 0.6719 | 0.6536 | 0.6719 | 0.6722    | 20.0    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.13.3