| --- |
| license: apache-2.0 |
| base_model: t5-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - multi_news |
| metrics: |
| - rouge |
| model-index: |
| - name: results |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| dataset: |
| name: multi_news |
| type: multi_news |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 37.35992631839289 |
| --- |
| |
| <!-- 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.9028 |
| - Rouge1: 37.3599 |
| - Rouge2: 12.1820 |
| - Rougel: 21.4068 |
| - Rougelsum: 21.3827 |
| - Gen Len: 141.366 |
| |
| ## 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-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | No log | 1.0 | 313 | 3.0888 | 33.8257 | 10.0913 | 19.3859 | 19.3966 | 131.264 | |
| | 3.487 | 2.0 | 626 | 3.0216 | 36.0141 | 11.1691 | 20.4601 | 20.4538 | 138.12 | |
| | 3.487 | 3.0 | 939 | 2.9906 | 36.2470 | 11.3578 | 20.6635 | 20.6692 | 138.632 | |
| | 3.2354 | 4.0 | 1252 | 2.9727 | 36.7252 | 11.5422 | 20.9492 | 20.9458 | 139.433 | |
| | 3.1863 | 5.0 | 1565 | 2.9586 | 36.6970 | 11.6533 | 20.9281 | 20.9236 | 140.189 | |
| | 3.1863 | 6.0 | 1878 | 2.9511 | 36.8584 | 11.7427 | 21.1395 | 21.1377 | 140.747 | |
| | 3.1624 | 7.0 | 2191 | 2.9441 | 36.9490 | 11.8362 | 21.2388 | 21.2508 | 140.994 | |
| | 3.1462 | 8.0 | 2504 | 2.9406 | 37.0855 | 11.8388 | 21.2447 | 21.2583 | 141.331 | |
| | 3.1462 | 9.0 | 2817 | 2.9383 | 37.0757 | 11.8588 | 21.2306 | 21.2472 | 140.901 | |
| | 3.1409 | 10.0 | 3130 | 2.9376 | 37.1450 | 11.9259 | 21.3013 | 21.3147 | 141.081 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.0 |
| - Pytorch 2.4.0 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
