--- license: mit base_model: indobenchmark/indobart-v2 tags: - generated_from_trainer datasets: - squad metrics: - rouge model-index: - name: modified-qa 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: 13.4458 --- # modified-qa 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: 3.9723 - Rouge1: 13.4458 - Rouge2: 6.819 - Rougel: 11.2064 - Rougelsum: 12.5476 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | 4.436 | 1.0 | 200 | 3.9723 | 13.4458 | 6.819 | 11.2064 | 12.5476 | 20.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.2 - Tokenizers 0.13.3