metadata
base_model: Ziyi98/T5-based-Masked-keywords-to-Sentence-Epoch-10
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: T5-based-Masked-keywords-to-Sentence-Epoch-100
results: []
T5-based-Masked-keywords-to-Sentence-Epoch-100
This model is a fine-tuned version of Ziyi98/T5-based-Masked-keywords-to-Sentence-Epoch-10 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.3610
- Bleu: 0.0608
- Gen Len: 16.6969
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 90
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 2.1627 | 1.0 | 527 | 2.3051 | 6.4693 | 13.3479 |
| 2.1432 | 2.0 | 1054 | 2.3051 | 6.411 | 13.334 |
| 2.1311 | 3.0 | 1581 | 2.3100 | 6.4619 | 13.3673 |
| 2.112 | 4.0 | 2108 | 2.3178 | 6.4873 | 13.3452 |
| 2.1025 | 5.0 | 2635 | 2.3190 | 6.4202 | 13.4955 |
| 2.0878 | 6.0 | 3162 | 2.3256 | 6.384 | 13.602 |
| 2.0761 | 7.0 | 3689 | 2.3266 | 6.4555 | 13.4283 |
| 2.0612 | 8.0 | 4216 | 2.3350 | 6.3692 | 13.5062 |
| 2.0522 | 9.0 | 4743 | 2.3411 | 6.1491 | 13.4014 |
| 2.0387 | 10.0 | 5270 | 2.3451 | 6.3275 | 13.5269 |
| 2.0295 | 11.0 | 5797 | 2.3464 | 6.334 | 13.5535 |
| 2.0157 | 12.0 | 6324 | 2.3460 | 6.3827 | 13.6229 |
| 2.0075 | 13.0 | 6851 | 2.3502 | 6.2845 | 13.4709 |
| 1.9982 | 14.0 | 7378 | 2.3546 | 6.2879 | 13.5585 |
| 1.988 | 15.0 | 7905 | 2.3568 | 6.2152 | 13.7016 |
| 1.9789 | 16.0 | 8432 | 2.3683 | 6.2631 | 13.6195 |
| 1.9705 | 17.0 | 8959 | 2.3671 | 6.2774 | 13.7046 |
| 1.9595 | 18.0 | 9486 | 2.3720 | 6.3235 | 13.6249 |
| 1.942 | 19.0 | 10013 | 2.3750 | 6.2509 | 13.664 |
| 1.9344 | 20.0 | 10540 | 2.3775 | 6.1464 | 13.7529 |
| 1.9256 | 21.0 | 11067 | 2.3831 | 6.1836 | 13.7041 |
| 1.9187 | 22.0 | 11594 | 2.3855 | 6.2706 | 13.732 |
| 1.9083 | 23.0 | 12121 | 2.3922 | 6.2403 | 13.6844 |
| 1.9042 | 24.0 | 12648 | 2.3880 | 6.2265 | 13.6294 |
| 1.8977 | 25.0 | 13175 | 2.3920 | 6.2174 | 13.7556 |
| 1.89 | 26.0 | 13702 | 2.3971 | 6.1378 | 13.7636 |
| 1.8829 | 27.0 | 14229 | 2.4059 | 6.1993 | 13.8609 |
| 1.878 | 28.0 | 14756 | 2.4021 | 6.2305 | 13.7735 |
| 1.8682 | 29.0 | 15283 | 2.4078 | 6.214 | 13.718 |
| 1.8633 | 30.0 | 15810 | 2.4144 | 6.1878 | 13.6239 |
| 1.8579 | 31.0 | 16337 | 2.4134 | 6.2359 | 13.767 |
| 1.8507 | 32.0 | 16864 | 2.4209 | 6.0733 | 13.7668 |
| 1.8476 | 33.0 | 17391 | 2.4219 | 6.1941 | 13.8415 |
| 1.8379 | 34.0 | 17918 | 2.4229 | 6.1035 | 13.8166 |
| 1.8344 | 35.0 | 18445 | 2.4191 | 6.006 | 13.8071 |
| 1.8288 | 36.0 | 18972 | 2.3862 | 6.1256 | 13.8425 |
| 1.8288 | 37.0 | 19499 | 2.3582 | 6.1404 | 13.6742 |
| 1.8957 | 38.0 | 20026 | 2.3621 | 6.1799 | 13.5436 |
| 1.9333 | 39.0 | 20553 | 2.3643 | 6.1766 | 13.3626 |
| 1.9881 | 40.0 | 21080 | 2.4340 | 6.0297 | 13.2076 |
| 2.2203 | 41.0 | 21607 | 2.6165 | 5.3393 | 12.3985 |
| 2.6689 | 42.0 | 22134 | 3.0787 | 3.7714 | 11.4059 |
| 3.3581 | 43.0 | 22661 | 3.3609 | 2.7532 | 10.8581 |
| 3.5599 | 44.0 | 23188 | 3.3780 | 2.7111 | 11.4898 |
| 3.5843 | 45.0 | 23715 | 3.4272 | 2.3855 | 12.0565 |
| 3.6436 | 46.0 | 24242 | 3.5025 | 2.1241 | 12.9236 |
| 3.8568 | 47.0 | 24769 | 4.8767 | 0.2474 | 12.2402 |
| 5.1045 | 48.0 | 25296 | 4.9483 | 0.1739 | 11.8688 |
| 5.3064 | 49.0 | 25823 | 4.8630 | 0.2754 | 11.5488 |
| 5.2256 | 50.0 | 26350 | 4.8141 | 0.31 | 11.4764 |
| 5.184 | 51.0 | 26877 | 4.7820 | 0.2611 | 11.6575 |
| 5.1601 | 52.0 | 27404 | 4.7407 | 0.2535 | 11.8586 |
| 5.1313 | 53.0 | 27931 | 4.7061 | 0.2523 | 12.1366 |
| 5.1018 | 54.0 | 28458 | 4.6740 | 0.243 | 12.4433 |
| 5.0831 | 55.0 | 28985 | 4.6411 | 0.2083 | 12.781 |
| 5.038 | 56.0 | 29512 | 4.6110 | 0.1449 | 13.1707 |
| 5.0216 | 57.0 | 30039 | 4.5820 | 0.2085 | 13.4438 |
| 5.0055 | 58.0 | 30566 | 4.5551 | 0.1939 | 13.8537 |
| 4.9907 | 59.0 | 31093 | 4.5303 | 0.1925 | 14.2357 |
| 4.9833 | 60.0 | 31620 | 4.5065 | 0.1827 | 14.6075 |
| 4.9686 | 61.0 | 32147 | 4.4851 | 0.1329 | 14.9664 |
| 4.9593 | 62.0 | 32674 | 4.4666 | 0.1243 | 15.4012 |
| 4.9555 | 63.0 | 33201 | 4.4485 | 0.0884 | 15.6971 |
| 4.9478 | 64.0 | 33728 | 4.4310 | 0.0706 | 15.9808 |
| 4.9386 | 65.0 | 34255 | 4.4103 | 0.0702 | 16.0742 |
| 4.9356 | 66.0 | 34782 | 4.3895 | 0.0709 | 16.2364 |
| 4.9207 | 67.0 | 35309 | 4.3738 | 0.0676 | 16.4515 |
| 4.9125 | 68.0 | 35836 | 4.3620 | 0.0636 | 16.6541 |
| 4.908 | 69.0 | 36363 | 4.3604 | 0.0625 | 16.6969 |
| 4.9133 | 70.0 | 36890 | 4.3605 | 0.0625 | 16.6829 |
| 4.9143 | 71.0 | 37417 | 4.3603 | 0.0625 | 16.6941 |
| 4.9108 | 72.0 | 37944 | 4.3602 | 0.0627 | 16.7096 |
| 4.9132 | 73.0 | 38471 | 4.3607 | 0.0629 | 16.6869 |
| 4.9128 | 74.0 | 38998 | 4.3607 | 0.0602 | 16.7173 |
| 4.9133 | 75.0 | 39525 | 4.3608 | 0.0602 | 16.7148 |
| 4.9114 | 76.0 | 40052 | 4.3609 | 0.0603 | 16.712 |
| 4.9101 | 77.0 | 40579 | 4.3610 | 0.0608 | 16.6969 |
| 4.9128 | 78.0 | 41106 | 4.3610 | 0.0608 | 16.6969 |
| 4.9106 | 79.0 | 41633 | 4.3610 | 0.0608 | 16.6969 |
| 4.9139 | 80.0 | 42160 | 4.3610 | 0.0608 | 16.6969 |
| 4.9145 | 81.0 | 42687 | 4.3610 | 0.0608 | 16.6969 |
| 4.9117 | 82.0 | 43214 | 4.3610 | 0.0608 | 16.6969 |
| 4.9153 | 83.0 | 43741 | 4.3610 | 0.0608 | 16.6969 |
| 4.9107 | 84.0 | 44268 | 4.3610 | 0.0608 | 16.6969 |
| 4.9139 | 85.0 | 44795 | 4.3610 | 0.0608 | 16.6969 |
| 4.9111 | 86.0 | 45322 | 4.3610 | 0.0608 | 16.6969 |
| 4.9101 | 87.0 | 45849 | 4.3610 | 0.0608 | 16.6969 |
| 4.9137 | 88.0 | 46376 | 4.3610 | 0.0608 | 16.6969 |
| 4.9142 | 89.0 | 46903 | 4.3610 | 0.0608 | 16.6969 |
| 4.913 | 90.0 | 47430 | 4.3610 | 0.0608 | 16.6969 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.1