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---
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
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