| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: summarizer |
| 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. --> |
|
|
| # summarizer |
|
|
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.5029 |
| - Rouge1: 48.685 |
| - Rouge2: 22.7386 |
| - Rougel: 43.8124 |
| - Rougelsum: 43.8396 |
|
|
| ## 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: 5.6e-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 |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | 2.3383 | 1.0 | 460 | 1.8745 | 49.3535 | 25.1806 | 45.1706 | 45.1579 | |
| | 1.5714 | 2.0 | 920 | 1.9525 | 48.5102 | 23.7917 | 43.5276 | 43.5289 | |
| | 1.0907 | 3.0 | 1380 | 2.0340 | 47.3071 | 22.9257 | 42.9624 | 43.0095 | |
| | 0.7586 | 4.0 | 1840 | 2.2207 | 49.078 | 24.4061 | 44.8266 | 44.7489 | |
| | 0.507 | 5.0 | 2300 | 2.3542 | 49.1445 | 23.918 | 44.4869 | 44.4544 | |
| | 0.3503 | 6.0 | 2760 | 2.4352 | 47.8282 | 22.9394 | 43.2666 | 43.2609 | |
| | 0.2434 | 7.0 | 3220 | 2.4867 | 48.8996 | 23.6147 | 44.4024 | 44.3788 | |
| | 0.1769 | 8.0 | 3680 | 2.5029 | 48.685 | 22.7386 | 43.8124 | 43.8396 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.28.1 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.3 |
|
|
