sc20fg/base_model_base_tokenizer

1---2license: apache-2.03base_model: t5-base4tags:5- generated_from_trainer6datasets:7- code_search_net8metrics:9- bleu10model-index:11- name: base_model_base_tokenizer12  results:13  - task:14      name: Sequence-to-sequence Language Modeling15      type: text2text-generation16    dataset:17      name: code_search_net18      type: code_search_net19      config: python20      split: test21      args: python22    metrics:23    - name: Bleu24      type: bleu25      value: 0.0743641462511342426---27 28<!-- This model card has been generated automatically according to the information the Trainer had access to. You29should probably proofread and complete it, then remove this comment. -->30 31# base_model_base_tokenizer32 33This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the code_search_net dataset.34It achieves the following results on the evaluation set:35- Loss: 2.101736- Bleu: 0.074437- Precisions: [0.37389569483256924, 0.14063645643779682, 0.07580332788787783, 0.045527148854836816]38- Brevity Penalty: 0.640739- Length Ratio: 0.692040- Translation Length: 58543641- Reference Length: 84605942 43## Model description44 45More information needed46 47## Intended uses & limitations48 49More information needed50 51## Training and evaluation data52 53More information needed54 55## Training procedure56 57### Training hyperparameters58 59The following hyperparameters were used during training:60- learning_rate: 2e-0561- train_batch_size: 1662- eval_batch_size: 1663- seed: 4264- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0865- lr_scheduler_type: linear66- num_epochs: 2067 68### Training results69 70| Training Loss | Epoch | Step   | Bleu   | Brevity Penalty | Length Ratio | Validation Loss | Precisions                                                                            | Reference Length | Translation Length |71|:-------------:|:-----:|:------:|:------:|:---------------:|:------------:|:---------------:|:-------------------------------------------------------------------------------------:|:----------------:|:------------------:|72| 2.4273        | 1.0   | 25762  | 0.0665 | 0.6794          | 0.7212       | 2.3438          | [0.34926724858481134, 0.12159425046725157, 0.062078959459937084, 0.03489467043820187] | 846059           | 610166             |73| 2.3512        | 2.0   | 51524  | 0.0733 | 0.7181          | 0.7512       | 2.2643          | [0.3534451290507329, 0.1262343107830303, 0.06531254968421979, 0.03721425521409004]    | 846059           | 635564             |74| 2.2525        | 3.0   | 77286  | 0.0691 | 0.6453          | 0.6954       | 2.2234          | [0.36523755211936504, 0.1318932094567742, 0.06891201805888993, 0.03961906221856018]   | 846059           | 588313             |75| 2.2252        | 4.0   | 103048 | 0.0726 | 0.7043          | 0.7404       | 2.1949          | [0.3601686933924165, 0.1283373434960897, 0.06578382296859486, 0.0371541685491374]     | 846059           | 626462             |76| 2.1523        | 5.0   | 128810 | 0.0703 | 0.6506          | 0.6994       | 2.1769          | [0.3663069159346027, 0.1334874876878427, 0.06959109409366254, 0.040003198275976946]   | 846059           | 591706             |77| 2.1027        | 6.0   | 154572 | 0.0650 | 0.5879          | 0.6531       | 2.1585          | [0.37335963586676196, 0.13614151644150174, 0.07119404952304512, 0.04138235959446398]  | 846059           | 552545             |78| 2.0458        | 7.0   | 180334 | 0.0682 | 0.6176          | 0.6748       | 2.1491          | [0.37062538973004405, 0.1355146147678402, 0.07123664846902444, 0.04155352506292986]   | 846059           | 570908             |79| 2.0594        | 8.0   | 206096 | 0.0702 | 0.6407          | 0.6919       | 2.1403          | [0.3700899171204657, 0.13524405355792343, 0.07062960711230036, 0.04081911815137772]   | 846059           | 585428             |80| 2.0459        | 9.0   | 231858 | 0.0635 | 0.5682          | 0.6388       | 2.1327          | [0.37916909499625345, 0.13810659289354987, 0.07176079868122479, 0.04160453545539102]  | 846059           | 540495             |81| 2.0029        | 10.0  | 257620 | 0.0684 | 0.6128          | 0.6713       | 2.1264          | [0.3745439691237164, 0.13731087325347474, 0.07204645620574554, 0.04194087964799725]   | 846059           | 567944             |82| 2.0107        | 11.0  | 283382 | 0.0697 | 0.6139          | 0.6721       | 2.1202          | [0.37538600600727345, 0.13908031254002817, 0.07356968494927149, 0.04326375560457764]  | 846059           | 568644             |83| 1.995         | 12.0  | 309144 | 0.0790 | 0.7220          | 0.7543       | 2.1192          | [0.3595232536092102, 0.1336969667453998, 0.07124298456393582, 0.04192048242921579]    | 846059           | 638159             |84| 1.9653        | 13.0  | 334906 | 0.0750 | 0.6727          | 0.7161       | 2.1158          | [0.3663186076760047, 0.13635359040297698, 0.07246562633002641, 0.04279559846361466]   | 846059           | 605836             |85| 1.9811        | 14.0  | 360668 | 0.0718 | 0.6325          | 0.6858       | 2.1096          | [0.37342310979981247, 0.13867710694415825, 0.0736328303569596, 0.043440268414579084]  | 846059           | 580256             |86| 1.9745        | 15.0  | 386430 | 0.0741 | 0.6592          | 0.7059       | 2.1060          | [0.36869699176985743, 0.13724429728380805, 0.07301699268383118, 0.04318353520566863]  | 846059           | 597195             |87| 1.939         | 16.0  | 412192 | 0.0706 | 0.6166          | 0.6740       | 2.1063          | [0.37537898781101553, 0.13979047848408885, 0.0742785001701673, 0.04399835661136439]   | 846059           | 570269             |88| 1.9177        | 17.0  | 437954 | 0.0757 | 0.6671          | 0.7118       | 2.1063          | [0.37017425883954735, 0.13833476986726426, 0.07389756751525232, 0.04386076232849102]  | 846059           | 602265             |89| 1.9265        | 18.0  | 463716 | 0.0717 | 0.6192          | 0.6760       | 2.1016          | [0.37650650333865443, 0.14089062050951845, 0.075366455530664, 0.045028150012067114]   | 846059           | 571937             |90| 1.9622        | 19.0  | 489478 | 0.0730 | 0.6288          | 0.6831       | 2.1022          | [0.3746837721013452, 0.1407333566053557, 0.07570910522025132, 0.045477562304123496]   | 846059           | 577906             |91| 1.9171        | 20.0  | 515240 | 2.1017 | 0.0744          | [0.37389569483256924, 0.14063645643779682, 0.07580332788787783, 0.045527148854836816]| 0.6407          | 0.6920                                                                                | 585436           | 846059             |92 93 94### Framework versions95 96- Transformers 4.37.297- Pytorch 2.2.0+cu12198- Datasets 2.17.099- Tokenizers 0.15.2100