--- base_model: google/pegasus-xsum tags: - generated_from_trainer model-index: - name: asril-pegasus-xlsum-skripsi results: [] --- # asril-pegasus-xlsum-skripsi This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.6919 ## Model description this model is spesifically for indonsesian abstractive news article summarization wich has been fine tuning in more than 48k dataset this model fine-tuned using pegasus model ## Intended uses & limitations More information needed ## Training and evaluation data xlsum/indonesian ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 4.5256 | 0.1046 | 1000 | 3.4857 | | 3.699 | 0.2092 | 2000 | 3.1625 | | 3.4046 | 0.3138 | 3000 | 2.9968 | | 3.2456 | 0.4184 | 4000 | 2.8834 | | 3.126 | 0.5230 | 5000 | 2.8127 | | 3.055 | 0.6275 | 6000 | 2.7644 | | 3.005 | 0.7321 | 7000 | 2.7281 | | 2.9597 | 0.8367 | 8000 | 2.7060 | | 2.9627 | 0.9413 | 9000 | 2.6919 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.1.0+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1