--- tags: - generated_from_trainer datasets: - data metrics: - bleu model-index: - name: mbart-en-id-smaller-indo-amr-generation-fted-with-prefix results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: data type: data config: default split: validation args: default metrics: - name: Bleu type: bleu value: 13.717 --- # mbart-en-id-smaller-indo-amr-generation-fted-with-prefix This model was trained from scratch on the data dataset. It achieves the following results on the evaluation set: - Loss: 2.3974 - Bleu: 13.717 - Gen Len: 36.5221 ## 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: 2e-07 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 12 - total_train_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: polynomial - lr_scheduler_warmup_steps: 200 - num_epochs: 16.0 - label_smoothing_factor: 0.1 ### Training results | Training Loss | Epoch | Step | Bleu | Gen Len | Validation Loss | |:-------------:|:-------:|:-----:|:-------:|:--------:|:---------------:| | 3.0219 | 0.9999 | 3869 | 0.0741 | 114.8177 | 2.9798 | | 2.8978 | 2.0 | 7739 | 0.0747 | 113.0081 | 2.8610 | | 2.8109 | 2.9999 | 11608 | 0.0795 | 111.475 | 2.7648 | | 2.7623 | 4.0 | 15478 | 0.1685 | 105.7747 | 2.6956 | | 2.7116 | 4.9999 | 19347 | 0.5081 | 92.4187 | 2.6404 | | 2.6331 | 5.9999 | 23214 | 1.6991 | 66.9245 | 2.5961 | | 2.5716 | 7.0 | 27084 | 5.2201 | 46.1405 | 2.5611 | | 2.5943 | 7.9999 | 30953 | 8.0263 | 40.7538 | 2.5300 | | 2.5622 | 9.0 | 34823 | 10.2353 | 38.2607 | 2.5050 | | 2.537 | 9.9999 | 38692 | 11.3364 | 36.0732 | 2.4840 | | 2.5345 | 11.0 | 42562 | 12.1716 | 36.4367 | 2.4645 | | 2.4706 | 11.9999 | 46428 | 2.4479 | 12.51 | 37.4146 | | 2.4558 | 13.0 | 50298 | 2.4330 | 12.8144 | 37.2979 | | 2.4125 | 13.9999 | 54167 | 2.4199 | 13.0772 | 37.0436 | | 2.4053 | 15.0 | 58037 | 2.4081 | 13.5764 | 36.1492 | | 2.439 | 15.9994 | 61904 | 2.3974 | 13.717 | 36.5221 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1