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--- |
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license: mit |
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base_model: unicamp-dl/ptt5-base-portuguese-vocab |
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tags: |
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- generated_from_trainer |
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datasets: |
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- xlsum |
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metrics: |
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- rouge |
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model-index: |
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- name: ptt5-xlsumm-30epochs |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: xlsum |
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type: xlsum |
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config: portuguese |
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split: test |
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args: portuguese |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.3246 |
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language: |
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- pt |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ptt5-xlsumm-30epochs |
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This model is a fine-tuned version of [unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-portuguese-vocab) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1787 |
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- Rouge1: 0.3246 |
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- Rouge2: 0.1471 |
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- Rougel: 0.2617 |
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- Rougelsum: 0.2641 |
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- Gen Len: 18.7065 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 2.5549 | 1.0 | 28701 | 2.2631 | 0.3049 | 0.1232 | 0.2416 | 0.2436 | 18.8318 | |
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| 2.4878 | 2.0 | 57402 | 2.2000 | 0.3134 | 0.1322 | 0.2497 | 0.2519 | 18.7965 | |
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| 2.3021 | 3.0 | 86103 | 2.1654 | 0.3161 | 0.1354 | 0.2528 | 0.255 | 18.732 | |
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| 2.2808 | 4.0 | 114804 | 2.1423 | 0.3179 | 0.1376 | 0.2544 | 0.2565 | 18.7217 | |
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| 2.2731 | 5.0 | 143505 | 2.1291 | 0.3202 | 0.1405 | 0.2567 | 0.259 | 18.7037 | |
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| 2.1654 | 6.0 | 172206 | 2.1209 | 0.3209 | 0.1417 | 0.2577 | 0.2598 | 18.6956 | |
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| 2.1716 | 7.0 | 200907 | 2.1173 | 0.3213 | 0.1423 | 0.2584 | 0.2606 | 18.7256 | |
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| 2.0696 | 8.0 | 229608 | 2.1136 | 0.3234 | 0.1441 | 0.2603 | 0.2627 | 18.7352 | |
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| 2.0492 | 9.0 | 258309 | 2.1123 | 0.3214 | 0.1425 | 0.2589 | 0.261 | 18.6357 | |
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| 2.0953 | 10.0 | 287010 | 2.1136 | 0.3244 | 0.146 | 0.2611 | 0.2634 | 18.7001 | |
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| 2.0358 | 11.0 | 315711 | 2.1180 | 0.3248 | 0.1466 | 0.2617 | 0.2639 | 18.6868 | |
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| 1.9475 | 12.0 | 344412 | 2.1191 | 0.3243 | 0.1463 | 0.2614 | 0.2637 | 18.6707 | |
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| 2.0194 | 13.0 | 373113 | 2.1181 | 0.3253 | 0.1466 | 0.2616 | 0.264 | 18.6939 | |
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| 1.925 | 14.0 | 401814 | 2.1236 | 0.3232 | 0.1454 | 0.2604 | 0.2629 | 18.6843 | |
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| 1.9194 | 15.0 | 430515 | 2.1294 | 0.3239 | 0.1464 | 0.2612 | 0.2636 | 18.6792 | |
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| 1.9163 | 16.0 | 459216 | 2.1301 | 0.3248 | 0.1464 | 0.261 | 0.2635 | 18.701 | |
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| 1.8482 | 17.0 | 487917 | 2.1366 | 0.325 | 0.1473 | 0.2619 | 0.2644 | 18.6786 | |
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| 1.8637 | 18.0 | 516618 | 2.1387 | 0.3263 | 0.1483 | 0.2624 | 0.2648 | 18.6811 | |
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| 1.8496 | 19.0 | 545319 | 2.1425 | 0.3244 | 0.1461 | 0.2613 | 0.2637 | 18.6934 | |
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| 1.8565 | 20.0 | 574020 | 2.1513 | 0.3257 | 0.1479 | 0.2626 | 0.2649 | 18.702 | |
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| 1.7683 | 21.0 | 602721 | 2.1559 | 0.3261 | 0.1482 | 0.2622 | 0.2646 | 18.718 | |
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| 1.7483 | 22.0 | 631422 | 2.1577 | 0.3254 | 0.1482 | 0.2625 | 0.2649 | 18.6939 | |
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| 1.7832 | 23.0 | 660123 | 2.1614 | 0.3234 | 0.147 | 0.2616 | 0.264 | 18.7033 | |
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| 1.8002 | 24.0 | 688824 | 2.1625 | 0.3246 | 0.1477 | 0.2626 | 0.2649 | 18.682 | |
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| 1.7381 | 25.0 | 717525 | 2.1689 | 0.3253 | 0.1473 | 0.2617 | 0.2641 | 18.7289 | |
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| 1.7367 | 26.0 | 746226 | 2.1677 | 0.3255 | 0.1475 | 0.2626 | 0.2649 | 18.7015 | |
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| 1.752 | 27.0 | 774927 | 2.1760 | 0.3255 | 0.1482 | 0.2631 | 0.2654 | 18.7146 | |
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| 1.7595 | 28.0 | 803628 | 2.1753 | 0.3241 | 0.1468 | 0.2616 | 0.264 | 18.7036 | |
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| 1.777 | 29.0 | 832329 | 2.1785 | 0.3246 | 0.1474 | 0.2618 | 0.2643 | 18.7089 | |
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| 1.7142 | 30.0 | 861030 | 2.1787 | 0.3246 | 0.1471 | 0.2617 | 0.2641 | 18.7065 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
