| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: final_bart_prepro_fix |
| 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_prepro_fix |
| |
| This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co/gogamza/kobart-base-v2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.6100 |
| - Rouge1: 35.5593 |
| - Rouge2: 13.0497 |
| - Rougel: 23.5672 |
| - Bleu1: 29.5206 |
| - Bleu2: 17.3914 |
| - Bleu3: 10.5577 |
| - Bleu4: 6.1502 |
| - Rdass: 0.6449 |
| - Gen Len: 49.7389 |
| |
| ## 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: 64 |
| - 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 | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Rdass | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:------:|:------:|:-------:| |
| | 2.1622 | 1.51 | 1000 | 2.6687 | 35.4366 | 12.8631 | 23.1588 | 29.4018 | 17.2004 | 10.3744 | 6.052 | 0.6379 | 49.4266 | |
| | 2.0114 | 3.02 | 2000 | 2.6090 | 35.1436 | 13.0347 | 23.4682 | 28.8917 | 17.0965 | 10.1873 | 5.896 | 0.6389 | 46.1096 | |
| | 1.8758 | 4.53 | 3000 | 2.6100 | 35.5593 | 13.0497 | 23.5672 | 29.5206 | 17.3914 | 10.5577 | 6.1502 | 0.6449 | 49.7389 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.25.1 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.7.1 |
| - Tokenizers 0.13.2 |
|
|
