--- license: mit base_model: indobenchmark/indobart-v2 tags: - generated_from_trainer datasets: - squad metrics: - rouge model-index: - name: results results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: squad type: squad config: plain_text split: train[:1000] args: plain_text metrics: - name: Rouge1 type: rouge value: 16.2693 --- # results This model is a fine-tuned version of [indobenchmark/indobart-v2](https://huggingface.co./indobenchmark/indobart-v2) on the squad dataset. It achieves the following results on the evaluation set: - Loss: 1.5998 - Rouge1: 16.2693 - Rouge2: 14.9952 - Rougel: 16.233 - Rougelsum: 16.2741 - Gen Len: 20.0 ## 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: 3e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 1 - label_smoothing_factor: 0.1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:------:|:---------:|:-------:| | 1.4819 | 1.0 | 200 | 1.5998 | 16.2693 | 14.9952 | 16.233 | 16.2741 | 20.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.2 - Tokenizers 0.13.3