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BART-CNN-Orangesum
Benjiccee/BART-CNN-Orangesum
BART-CNN-Orangesum is a summarization model from Benjiccee. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as mit.
This model is a fine-tuned version of facebook/bart-large-cnn on the orangesum dataset. It achieves the following results on the evaluation set: - Loss: 1.6370
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At a glance
- Task
- Summarization
- Library
- transformers
- License
- mit
- Model type
- bart
- Access
- Public
- Created
- Jul 30, 2023
- Updated
- Aug 24, 2023
- SHA
- c96420ce
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Datasets
Model card
From the Hugging Face model README
BART-CNN-Orangesum
This model is a fine-tuned version of 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
- Task
- Summarization
- Library
- transformers
- Type
- bart
- License
- mit
- Languages
- fr, en
- Created
- Jul 30, 2023
- Updated
- Aug 24, 2023