--- license: apache-2.0 base_model: facebook/bart-base tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-base-finetuned-cnn_dailymail results: [] --- # bart-base-finetuned-cnn_dailymail This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0624 - Rouge1: 24.4564 - Rouge2: 11.9696 - Rougel: 20.5207 - Rougelsum: 23.0078 - Bleu 1: 4.1113 - Bleu 2: 2.692 - Bleu 3: 1.9585 - Meteor: 12.0483 - Compression rate: 4.07 ## 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: 5.6e-05 - train_batch_size: 16 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 6 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Compression rate | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:------:|:------:|:------:|:-------:|:----------------:| | 1.3117 | 1.0 | 1875 | 1.0873 | 24.4119 | 11.8902 | 20.5092 | 22.8997 | 4.1432 | 2.7081 | 1.9647 | 12.0394 | 4.0945 | | 1.0667 | 2.0 | 3750 | 1.0588 | 24.364 | 11.9692 | 20.3498 | 22.8133 | 4.0425 | 2.6521 | 1.9328 | 11.9475 | 4.1164 | | 0.9644 | 3.0 | 5625 | 1.0564 | 24.2853 | 11.9445 | 20.4585 | 22.8519 | 4.0533 | 2.6698 | 1.9457 | 11.9912 | 4.1173 | | 0.8876 | 4.0 | 7500 | 1.0519 | 24.2696 | 11.8337 | 20.3562 | 22.8098 | 4.1164 | 2.698 | 1.9479 | 11.9819 | 4.0777 | | 0.8301 | 5.0 | 9375 | 1.0556 | 24.393 | 11.9329 | 20.4502 | 22.9487 | 4.116 | 2.693 | 1.9458 | 11.9937 | 4.0738 | | 0.7897 | 6.0 | 11250 | 1.0624 | 24.4564 | 11.9696 | 20.5207 | 23.0078 | 4.1113 | 2.692 | 1.9585 | 12.0483 | 4.07 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.2.2+cu118 - Datasets 2.19.0 - Tokenizers 0.19.1