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ptt5-wikilingua-cstnews
This model is a fine-tuned version of arthurmluz/ptt5-wikilingua-30epochs on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2336
- Rouge1: 0.2757
- Rouge2: 0.2182
- Rougel: 0.2534
- Rougelsum: 0.2727
- Gen Len: 19.0
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 47 | 1.4403 | 0.2059 | 0.1334 | 0.1769 | 0.1998 | 18.6452 |
| No log | 2.0 | 94 | 1.3259 | 0.2356 | 0.1632 | 0.2052 | 0.2286 | 18.871 |
| No log | 3.0 | 141 | 1.2783 | 0.244 | 0.1737 | 0.215 | 0.2331 | 18.871 |
| No log | 4.0 | 188 | 1.2469 | 0.2518 | 0.1866 | 0.2174 | 0.2366 | 18.9355 |
| 1.7624 | 5.0 | 235 | 1.2306 | 0.266 | 0.1958 | 0.2321 | 0.2539 | 18.9355 |
| 1.7624 | 6.0 | 282 | 1.2214 | 0.2644 | 0.1991 | 0.2347 | 0.2533 | 18.9355 |
| 1.7624 | 7.0 | 329 | 1.2133 | 0.2603 | 0.1975 | 0.2327 | 0.2505 | 18.9355 |
| 1.7624 | 8.0 | 376 | 1.2076 | 0.267 | 0.2058 | 0.2423 | 0.2589 | 18.9355 |
| 1.3494 | 9.0 | 423 | 1.2026 | 0.2698 | 0.2073 | 0.2454 | 0.2643 | 18.9355 |
| 1.3494 | 10.0 | 470 | 1.1997 | 0.2704 | 0.2078 | 0.2457 | 0.2649 | 19.0 |
| 1.3494 | 11.0 | 517 | 1.2006 | 0.2762 | 0.2151 | 0.2518 | 0.2736 | 19.0 |
| 1.3494 | 12.0 | 564 | 1.2012 | 0.2772 | 0.2163 | 0.2545 | 0.2746 | 19.0 |
| 1.1715 | 13.0 | 611 | 1.2017 | 0.2787 | 0.2176 | 0.2555 | 0.2763 | 19.0 |
| 1.1715 | 14.0 | 658 | 1.2048 | 0.278 | 0.2187 | 0.256 | 0.2753 | 19.0 |
| 1.1715 | 15.0 | 705 | 1.2063 | 0.2755 | 0.2219 | 0.2579 | 0.2735 | 19.0 |
| 1.1715 | 16.0 | 752 | 1.2057 | 0.2768 | 0.2219 | 0.2589 | 0.2748 | 19.0 |
| 1.1715 | 17.0 | 799 | 1.2084 | 0.2798 | 0.2244 | 0.26 | 0.2783 | 19.0 |
| 1.0497 | 18.0 | 846 | 1.2138 | 0.2787 | 0.2258 | 0.2602 | 0.2764 | 19.0 |
| 1.0497 | 19.0 | 893 | 1.2177 | 0.2783 | 0.2248 | 0.26 | 0.2761 | 19.0 |
| 1.0497 | 20.0 | 940 | 1.2166 | 0.2767 | 0.2215 | 0.2583 | 0.2745 | 19.0 |
| 1.0497 | 21.0 | 987 | 1.2187 | 0.2738 | 0.2162 | 0.2527 | 0.2715 | 19.0 |
| 0.9439 | 22.0 | 1034 | 1.2196 | 0.2741 | 0.2171 | 0.2531 | 0.2718 | 19.0 |
| 0.9439 | 23.0 | 1081 | 1.2229 | 0.2741 | 0.2171 | 0.2531 | 0.2718 | 19.0 |
| 0.9439 | 24.0 | 1128 | 1.2257 | 0.2757 | 0.2182 | 0.2534 | 0.2727 | 19.0 |
| 0.9439 | 25.0 | 1175 | 1.2292 | 0.2739 | 0.2171 | 0.2525 | 0.2713 | 19.0 |
| 0.8986 | 26.0 | 1222 | 1.2294 | 0.2739 | 0.2171 | 0.2525 | 0.2713 | 19.0 |
| 0.8986 | 27.0 | 1269 | 1.2310 | 0.2767 | 0.2192 | 0.2548 | 0.2741 | 19.0 |
| 0.8986 | 28.0 | 1316 | 1.2325 | 0.2747 | 0.218 | 0.2536 | 0.2725 | 19.0 |
| 0.8986 | 29.0 | 1363 | 1.2335 | 0.2739 | 0.2171 | 0.2525 | 0.2713 | 19.0 |
| 0.8805 | 30.0 | 1410 | 1.2336 | 0.2757 | 0.2182 | 0.2534 | 0.2727 | 19.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
