| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: final_bart | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # final_bart | |
| This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co/gogamza/kobart-base-v2) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 2.6848 | |
| - Rouge1: 35.7722 | |
| - Rouge2: 12.5127 | |
| - Rougel: 23.3002 | |
| - Rdass: 0.6248 | |
| - Bleu1: 30.5261 | |
| - Bleu2: 17.6264 | |
| - Bleu3: 10.3974 | |
| - Bleu4: 5.4348 | |
| - Gen Len: 53.47 | |
| ## 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: 64 | |
| - eval_batch_size: 128 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 5.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rdass | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:------:|:-------:|:-------:|:-------:|:------:|:-------:| | |
| | 2.1542 | 1.5 | 1000 | 2.7491 | 33.5554 | 11.2371 | 22.006 | 0.6093 | 27.9938 | 15.5354 | 8.2494 | 4.42 | 50.08 | | |
| | 2.0071 | 2.99 | 2000 | 2.6813 | 35.0501 | 12.2759 | 22.6669 | 0.6155 | 29.6866 | 17.1396 | 9.7016 | 5.3559 | 54.04 | | |
| | 1.8694 | 4.49 | 3000 | 2.6848 | 35.7722 | 12.5127 | 23.3002 | 0.6248 | 30.5261 | 17.6264 | 10.3974 | 5.4348 | 53.47 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.7.1 | |
| - Tokenizers 0.13.2 | |