--- tags: - generated_from_trainer metrics: - rouge model-index: - name: bart-base-finetuned-cnn_dailymail results: [] --- # bart-base-finetuned-cnn_dailymail This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0513 - Rouge1: 24.267 - Rouge2: 11.7305 - Rougel: 20.2444 - Rougelsum: 22.6768 - Bleu 1: 4.2724 - Bleu 2: 2.7858 - Bleu 3: 2.0352 - Meteor: 12.0395 - Compression rate: 4.0329 ## 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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Compression rate | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:---------:|:------:|:------:|:------:|:-------:|:----------------:| | 1.1979 | 1.0 | 625 | 1.0653 | 23.882 | 11.5236 | 19.9616 | 22.36 | 4.1676 | 2.7136 | 1.9845 | 11.8215 | 4.0625 | | 1.0449 | 2.0 | 1250 | 1.0513 | 24.267 | 11.7305 | 20.2444 | 22.6768 | 4.2724 | 2.7858 | 2.0352 | 12.0395 | 4.0329 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.2.2+cu118 - Datasets 2.19.0 - Tokenizers 0.19.1