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ptt5-wikilingua-cstnews-1024
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: 1.1062
- Rouge1: 0.2634
- Rouge2: 0.2049
- Rougel: 0.2461
- Rougelsum: 0.2619
- Gen Len: 18.871
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 | 1.3346 | 0.1918 | 0.1194 | 0.161 | 0.1857 | 18.6452 |
| No log | 2.0 | 94 | 1.2279 | 0.2326 | 0.1626 | 0.1996 | 0.2285 | 18.871 |
| No log | 3.0 | 141 | 1.1763 | 0.2424 | 0.1692 | 0.2117 | 0.2381 | 18.871 |
| No log | 4.0 | 188 | 1.1496 | 0.2467 | 0.1761 | 0.2129 | 0.2347 | 18.871 |
| 1.727 | 5.0 | 235 | 1.1292 | 0.2579 | 0.188 | 0.2317 | 0.2515 | 18.871 |
| 1.727 | 6.0 | 282 | 1.1190 | 0.2516 | 0.1834 | 0.2256 | 0.2435 | 18.871 |
| 1.727 | 7.0 | 329 | 1.1059 | 0.2476 | 0.1806 | 0.2227 | 0.2404 | 18.871 |
| 1.727 | 8.0 | 376 | 1.0990 | 0.2468 | 0.1797 | 0.2217 | 0.2391 | 18.871 |
| 1.3202 | 9.0 | 423 | 1.0910 | 0.2587 | 0.1902 | 0.2339 | 0.2541 | 18.871 |
| 1.3202 | 10.0 | 470 | 1.0882 | 0.259 | 0.1908 | 0.2343 | 0.2545 | 18.871 |
| 1.3202 | 11.0 | 517 | 1.0885 | 0.2539 | 0.1886 | 0.2324 | 0.2505 | 18.871 |
| 1.3202 | 12.0 | 564 | 1.0883 | 0.2601 | 0.1957 | 0.2399 | 0.2582 | 18.871 |
| 1.1493 | 13.0 | 611 | 1.0881 | 0.2607 | 0.1962 | 0.2403 | 0.2583 | 18.871 |
| 1.1493 | 14.0 | 658 | 1.0866 | 0.2624 | 0.1976 | 0.2433 | 0.26 | 18.871 |
| 1.1493 | 15.0 | 705 | 1.0875 | 0.2641 | 0.2072 | 0.2477 | 0.2626 | 18.871 |
| 1.1493 | 16.0 | 752 | 1.0897 | 0.2641 | 0.2069 | 0.2477 | 0.2626 | 18.871 |
| 1.1493 | 17.0 | 799 | 1.0913 | 0.2641 | 0.2072 | 0.2477 | 0.2626 | 18.871 |
| 1.0308 | 18.0 | 846 | 1.0927 | 0.2634 | 0.2063 | 0.2474 | 0.2618 | 18.871 |
| 1.0308 | 19.0 | 893 | 1.0977 | 0.2634 | 0.2059 | 0.2473 | 0.2618 | 18.871 |
| 1.0308 | 20.0 | 940 | 1.0976 | 0.2634 | 0.2059 | 0.2473 | 0.2618 | 18.871 |
| 1.0308 | 21.0 | 987 | 1.0993 | 0.2632 | 0.2059 | 0.247 | 0.2616 | 18.871 |
| 0.9401 | 22.0 | 1034 | 1.1000 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.9401 | 23.0 | 1081 | 1.0997 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.9401 | 24.0 | 1128 | 1.1018 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.9401 | 25.0 | 1175 | 1.1045 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.8857 | 26.0 | 1222 | 1.1057 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.8857 | 27.0 | 1269 | 1.1061 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.8857 | 28.0 | 1316 | 1.1062 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.8857 | 29.0 | 1363 | 1.1061 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
| 0.8716 | 30.0 | 1410 | 1.1062 | 0.2634 | 0.2049 | 0.2461 | 0.2619 | 18.871 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
