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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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metrics: |
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- rouge |
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model-index: |
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- name: ptt5-wikilingua-30epochs |
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results: [] |
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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-wikilingua-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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9063 |
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- Rouge1: 0.2604 |
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- Rouge2: 0.1127 |
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- Rougel: 0.2222 |
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- Rougelsum: 0.2541 |
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- Gen Len: 18.4528 |
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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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| 2.1668 | 1.0 | 28580 | 2.0384 | 0.2366 | 0.0935 | 0.2034 | 0.2311 | 18.2195 | |
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| 2.0348 | 2.0 | 57160 | 1.9725 | 0.2448 | 0.0998 | 0.2098 | 0.2391 | 18.3898 | |
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| 2.0152 | 3.0 | 85740 | 1.9346 | 0.2469 | 0.1024 | 0.2122 | 0.2414 | 18.2427 | |
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| 1.9769 | 4.0 | 114320 | 1.9096 | 0.2503 | 0.1047 | 0.2147 | 0.2446 | 18.2773 | |
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| 1.8471 | 5.0 | 142900 | 1.8957 | 0.253 | 0.1076 | 0.2169 | 0.2473 | 18.2612 | |
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| 1.8504 | 6.0 | 171480 | 1.8840 | 0.2541 | 0.1084 | 0.2179 | 0.2483 | 18.3317 | |
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| 1.7456 | 7.0 | 200060 | 1.8768 | 0.2547 | 0.1084 | 0.2183 | 0.2488 | 18.3634 | |
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| 1.7254 | 8.0 | 228640 | 1.8747 | 0.2563 | 0.1099 | 0.2196 | 0.2505 | 18.3577 | |
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| 1.7742 | 9.0 | 257220 | 1.8739 | 0.2562 | 0.11 | 0.2194 | 0.2504 | 18.3904 | |
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| 1.7211 | 10.0 | 285800 | 1.8667 | 0.2572 | 0.1109 | 0.2205 | 0.2513 | 18.3616 | |
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| 1.696 | 11.0 | 314380 | 1.8677 | 0.2568 | 0.1112 | 0.2204 | 0.251 | 18.349 | |
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| 1.6762 | 12.0 | 342960 | 1.8695 | 0.2571 | 0.1108 | 0.2202 | 0.2513 | 18.3528 | |
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| 1.6404 | 13.0 | 371540 | 1.8738 | 0.2582 | 0.1115 | 0.2208 | 0.2523 | 18.3909 | |
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| 1.6523 | 14.0 | 400120 | 1.8727 | 0.259 | 0.1118 | 0.2215 | 0.253 | 18.4077 | |
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| 1.626 | 15.0 | 428700 | 1.8736 | 0.2596 | 0.1124 | 0.2222 | 0.2537 | 18.4245 | |
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| 1.5922 | 16.0 | 457280 | 1.8750 | 0.259 | 0.1123 | 0.2215 | 0.253 | 18.4125 | |
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| 1.5345 | 17.0 | 485860 | 1.8783 | 0.2591 | 0.112 | 0.2214 | 0.2529 | 18.4013 | |
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| 1.5785 | 18.0 | 514440 | 1.8797 | 0.2588 | 0.112 | 0.2212 | 0.2527 | 18.3965 | |
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| 1.5097 | 19.0 | 543020 | 1.8868 | 0.2592 | 0.1115 | 0.221 | 0.2531 | 18.4567 | |
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| 1.5091 | 20.0 | 571600 | 1.8851 | 0.2593 | 0.1124 | 0.2216 | 0.2533 | 18.397 | |
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| 1.5116 | 21.0 | 600180 | 1.8895 | 0.2599 | 0.1124 | 0.2219 | 0.2537 | 18.4505 | |
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| 1.5351 | 22.0 | 628760 | 1.8901 | 0.2606 | 0.113 | 0.2225 | 0.2544 | 18.4369 | |
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| 1.5125 | 23.0 | 657340 | 1.8953 | 0.2598 | 0.1125 | 0.2218 | 0.2535 | 18.4273 | |
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| 1.5246 | 24.0 | 685920 | 1.8980 | 0.2609 | 0.1129 | 0.2226 | 0.2544 | 18.4464 | |
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| 1.5113 | 25.0 | 714500 | 1.8990 | 0.2604 | 0.1127 | 0.2221 | 0.2542 | 18.4562 | |
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| 1.4814 | 26.0 | 743080 | 1.9029 | 0.261 | 0.1133 | 0.223 | 0.2547 | 18.4634 | |
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| 1.5212 | 27.0 | 771660 | 1.9014 | 0.2606 | 0.1129 | 0.2226 | 0.2544 | 18.4458 | |
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| 1.4469 | 28.0 | 800240 | 1.9032 | 0.2609 | 0.1129 | 0.2226 | 0.2546 | 18.4577 | |
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| 1.4844 | 29.0 | 828820 | 1.9050 | 0.2602 | 0.1125 | 0.2221 | 0.2539 | 18.4553 | |
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| 1.4561 | 30.0 | 857400 | 1.9063 | 0.2604 | 0.1127 | 0.2222 | 0.2541 | 18.4528 | |
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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 |
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