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--- |
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language: |
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- de |
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tags: |
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- question-generation |
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- german |
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- text2text-generation |
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- generated_from_trainer |
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datasets: |
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- lmqg/qg_dequad |
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metrics: |
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- bleu4 |
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- f1 |
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- rouge |
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- exact_match |
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model-index: |
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- name: german-jeopardy-longt5-large-256 |
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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: lmqg/qg_dequad |
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type: default |
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args: default |
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metrics: |
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- name: BLEU-4 |
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type: bleu4 |
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value: 4.87 |
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- name: F1 |
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type: f1 |
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value: 23.82 |
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- name: ROUGE-1 |
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type: rouge1 |
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value: 23.88 |
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- name: ROUGE-2 |
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type: rouge2 |
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value: 8.54 |
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- name: ROUGE-L |
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type: rougel |
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value: 23.14 |
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- name: ROUGE-Lsum |
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type: rougelsum |
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value: 23.13 |
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- name: Exact Match |
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type: exact_match |
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value: 0.32 |
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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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# german-jeopardy-longt5-large-256 |
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This model is a fine-tuned version of [google/long-t5-tglobal-large](https://huggingface.co/google/long-t5-tglobal-large) on the [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8541 |
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- Brevity Penalty: 0.8795 |
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- System Length: 18427 |
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- Reference Length: 20793 |
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- ROUGE-1: 23.88 |
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- ROUGE-2: 8.54 |
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- ROUGE-L: 23.14 |
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- ROUGE-Lsum: 23.13 |
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- Exact Match: 0.32 |
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- BLEU: 4.87 |
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- F1: 23.82 |
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## Model description |
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See [google/long-t5-tglobal-large](https://huggingface.co/google/long-t5-tglobal-large) for more information about the |
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model architecture. |
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The model was trained on a single NVIDIA RTX 3090 GPU with 24GB of VRAM. |
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## Intended uses & limitations |
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This model can be used for question generation on German text. |
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## Training and evaluation data |
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See [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad). |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 7 |
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- gradient_accumulation_steps: 128 |
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- total_train_batch_size: 256 |
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- optimizer: Adafactor |
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- lr_scheduler_type: constant |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Counts 1 | Counts 2 | Counts 3 | Counts 4 | Totals 1 | Totals 2 | Totals 3 | Totals 4 | Precisions 1 | Precisions 2 | Precisions 3 | Precisions 4 | Brevity Penalty | System Length | Reference Length | ROUGE-1 | ROUGE-2 | ROUGE-L | ROUGE-Lsum | Exact Match | BLEU | Mean Generated Length | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:----------------:|:-------:|:-------:|:-------:|:----------:|:-----------:|:------:|:---------------------:|:------:| |
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| 8.8727 | 0.99 | 36 | 6.3810 | 2198 | 0 | 0 | 0 | 2204 | 0 | 0 | 0 | 99.7278 | 0.0 | 0.0 | 0.0 | 0.0002 | 2204 | 21250 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | |
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| 6.0165 | 1.98 | 72 | 5.3864 | 3587 | 137 | 0 | 0 | 21960 | 19756 | 17552 | 15348 | 16.3342 | 0.6935 | 0.0028 | 0.0016 | 1.0 | 21960 | 21250 | 0.0702 | 0.0079 | 0.07 | 0.07 | 0.0 | 0.0851 | 15.0091 | 0.073 | |
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| 5.1537 | 3.0 | 109 | 4.9617 | 3601 | 145 | 1 | 0 | 14449 | 12245 | 10041 | 7837 | 24.9221 | 1.1842 | 0.01 | 0.0064 | 0.6246 | 14449 | 21250 | 0.0882 | 0.0107 | 0.0877 | 0.0876 | 0.0 | 0.13 | 9.5309 | 0.0926 | |
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| 4.863 | 3.99 | 145 | 4.5531 | 4590 | 229 | 19 | 0 | 41674 | 39470 | 37266 | 35062 | 11.0141 | 0.5802 | 0.051 | 0.0014 | 1.0 | 41674 | 21250 | 0.0811 | 0.0081 | 0.0768 | 0.0767 | 0.0 | 0.1468 | 29.4528 | 0.0836 | |
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| 4.5201 | 4.97 | 181 | 4.2020 | 3643 | 169 | 19 | 0 | 16104 | 13900 | 11696 | 9492 | 22.6217 | 1.2158 | 0.1624 | 0.0053 | 0.7265 | 16104 | 21250 | 0.0865 | 0.0115 | 0.0856 | 0.0855 | 0.0 | 0.2845 | 12.5077 | 0.0907 | |
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| 4.1347 | 5.99 | 218 | 3.9353 | 3670 | 167 | 20 | 0 | 16796 | 14592 | 12388 | 10184 | 21.8504 | 1.1445 | 0.1614 | 0.0049 | 0.7671 | 16796 | 21250 | 0.087 | 0.0114 | 0.0859 | 0.0858 | 0.0 | 0.2878 | 13.1656 | 0.0917 | |
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| 4.012 | 6.98 | 254 | 3.7593 | 3780 | 198 | 35 | 1 | 16582 | 14378 | 12174 | 9970 | 22.7958 | 1.3771 | 0.2875 | 0.01 | 0.7546 | 16582 | 21250 | 0.0916 | 0.0128 | 0.0903 | 0.0902 | 0.0 | 0.4139 | 12.2931 | 0.0968 | |
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| 3.7048 | 8.0 | 291 | 3.6034 | 3668 | 205 | 36 | 3 | 16158 | 13954 | 11750 | 9546 | 22.7008 | 1.4691 | 0.3064 | 0.0314 | 0.7297 | 16158 | 21250 | 0.0882 | 0.0134 | 0.0873 | 0.0872 | 0.0 | 0.5493 | 11.7568 | 0.0923 | |
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| 3.6284 | 8.99 | 327 | 3.4567 | 4070 | 527 | 160 | 28 | 17459 | 15255 | 13051 | 10847 | 23.3118 | 3.4546 | 1.226 | 0.2581 | 0.8048 | 17459 | 21250 | 0.1109 | 0.0281 | 0.1083 | 0.1082 | 0.0 | 1.8083 | 9.7777 | 0.1152 | |
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| 3.4605 | 9.98 | 363 | 3.3390 | 4325 | 512 | 128 | 27 | 18829 | 16625 | 14421 | 12217 | 22.9699 | 3.0797 | 0.8876 | 0.221 | 0.8793 | 18829 | 21250 | 0.1206 | 0.0288 | 0.1168 | 0.1167 | 0.0 | 1.6972 | 12.6729 | 0.1254 | |
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| 3.2267 | 10.99 | 400 | 3.1995 | 4498 | 774 | 237 | 49 | 18802 | 16598 | 14394 | 12190 | 23.923 | 4.6632 | 1.6465 | 0.402 | 0.8779 | 18802 | 21250 | 0.1348 | 0.0405 | 0.132 | 0.1319 | 0.0005 | 2.5735 | 11.5009 | 0.1381 | |
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| 3.1761 | 11.98 | 436 | 3.1165 | 4578 | 866 | 260 | 50 | 16963 | 14759 | 12555 | 10351 | 26.9882 | 5.8676 | 2.0709 | 0.483 | 0.7767 | 16963 | 21250 | 0.1454 | 0.0464 | 0.1426 | 0.1427 | 0.0005 | 2.7554 | 10.5172 | 0.1492 | |
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| 3.0323 | 12.97 | 472 | 3.0074 | 5019 | 1048 | 319 | 59 | 18077 | 15873 | 13669 | 11465 | 27.7646 | 6.6024 | 2.3337 | 0.5146 | 0.839 | 18077 | 21250 | 0.1691 | 0.0557 | 0.1648 | 0.1647 | 0.0009 | 3.2318 | 12.8294 | 0.1729 | |
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| 2.8223 | 13.99 | 509 | 2.8911 | 5257 | 1120 | 341 | 85 | 17074 | 14870 | 12666 | 10462 | 30.7895 | 7.5319 | 2.6922 | 0.8125 | 0.783 | 17074 | 21250 | 0.189 | 0.0635 | 0.1841 | 0.184 | 0.0018 | 3.7161 | 12.6824 | 0.1929 | |
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| 2.7732 | 14.98 | 545 | 2.8103 | 5616 | 1271 | 407 | 113 | 17784 | 15580 | 13376 | 11172 | 31.5789 | 8.1579 | 3.0428 | 1.0115 | 0.8229 | 17784 | 21250 | 0.2122 | 0.0731 | 0.2063 | 0.2061 | 0.0045 | 4.3667 | 13.0944 | 0.217 | |
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| 2.58 | 16.0 | 582 | 2.7183 | 5959 | 1461 | 510 | 171 | 18808 | 16604 | 14400 | 12196 | 31.6833 | 8.7991 | 3.5417 | 1.4021 | 0.8782 | 18808 | 21250 | 0.2286 | 0.0822 | 0.2214 | 0.2212 | 0.0064 | 5.357 | 13.9174 | 0.2316 | |
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| 2.5368 | 16.99 | 618 | 2.6630 | 5935 | 1543 | 576 | 201 | 16923 | 14719 | 12515 | 10311 | 35.0706 | 10.483 | 4.6025 | 1.9494 | 0.7744 | 16923 | 21250 | 0.2365 | 0.089 | 0.2309 | 0.2307 | 0.0059 | 5.8686 | 12.3185 | 0.2377 | |
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| 2.4325 | 17.98 | 654 | 2.5798 | 6305 | 1756 | 685 | 265 | 17870 | 15666 | 13462 | 11258 | 35.2826 | 11.209 | 5.0884 | 2.3539 | 0.8277 | 17870 | 21250 | 0.2518 | 0.0982 | 0.2452 | 0.2452 | 0.0059 | 6.8664 | 13.1688 | 0.2537 | |
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| 2.2632 | 18.99 | 691 | 2.5155 | 6577 | 1888 | 762 | 304 | 17785 | 15581 | 13377 | 11173 | 36.9806 | 12.1173 | 5.6963 | 2.7208 | 0.823 | 17785 | 21250 | 0.2689 | 0.1102 | 0.261 | 0.2611 | 0.0086 | 7.5129 | 13.2373 | 0.2702 | |
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| 2.2026 | 19.79 | 720 | 2.4997 | 6644 | 1853 | 720 | 273 | 17658 | 15454 | 13250 | 11046 | 37.626 | 11.9904 | 5.434 | 2.4715 | 0.8159 | 17658 | 21250 | 0.2717 | 0.1097 | 0.2628 | 0.2625 | 0.0073 | 7.1987 | 13.6343 | 0.2742 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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