--- license: mit library_name: peft tags: - generated_from_trainer base_model: percymamedy/bart-cnn-samsum-finetuned datasets: - samsum model-index: - name: bart-cnn-samsum-peft results: [] --- # bart-cnn-samsum-peft This model is a fine-tuned version of [percymamedy/bart-cnn-samsum-finetuned](https://huggingface.co/percymamedy/bart-cnn-samsum-finetuned) on the samsum dataset. It achieves the following results on the evaluation set: - Loss: 0.1343 ## 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: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.078 | 1.0 | 19 | 0.1347 | | 0.0865 | 2.0 | 38 | 0.1346 | | 0.0768 | 3.0 | 57 | 0.1345 | | 0.0789 | 4.0 | 76 | 0.1344 | | 0.0914 | 5.0 | 95 | 0.1344 | | 0.0835 | 6.0 | 114 | 0.1343 | | 0.0865 | 7.0 | 133 | 0.1343 | | 0.0806 | 8.0 | 152 | 0.1343 | | 0.0884 | 9.0 | 171 | 0.1343 | | 0.0934 | 10.0 | 190 | 0.1343 | ### Framework versions - PEFT 0.11.1 - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1