--- language: - fr - en license: mit tags: - generated_from_trainer - summarization datasets: - orange_sum base_model: facebook/bart-large-cnn model-index: - name: BART-CNN-Orangesum results: [] --- # 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