File size: 1,509 Bytes
149496d f21dfc7 149496d c96420c 149496d 37f6473 149496d f21dfc7 37f6473 149496d f21dfc7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
---
license: mit
tags:
- generated_from_trainer
- summarization
datasets:
- orange_sum
model-index:
- name: BART-CNN-Orangesum
results: []
language:
- fr
- en
---
# BART-CNN-Orangesum
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the orange_sum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6370
It aims at improving the quality of the summary generated on French texts
## Model description
this is a fine tuning of the model 'facebook/bart-large-cnn' on the 'orange_sum' dataset
gives better results in French while keeping the intrinsic qualities of the BART model
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9062 | 0.37 | 500 | 1.8412 |
| 1.6596 | 0.75 | 1000 | 1.6370 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3 |