--- license: bsd-3-clause base_model: Salesforce/codet5p-770m-py tags: - generated_from_trainer datasets: - mbpp model-index: - name: codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_1 results: [] --- # codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_1 This model is a fine-tuned version of [Salesforce/codet5p-770m-py](https://huggingface.co/Salesforce/codet5p-770m-py) on the mbpp dataset. It achieves the following results on the evaluation set: - Loss: 0.7230 - Codebleu: 0.0971 - Ngram Match Score: 0.0163 - Weighted Ngram Match Score: 0.0411 - Syntax Match Score: 0.1058 - Dataflow Match Score: 0.1225 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 64 ### Training results | Training Loss | Epoch | Step | Validation Loss | Codebleu | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:| | 0.9754 | 1.0 | 15 | 0.9244 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9686 | 2.0 | 30 | 0.9226 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9714 | 3.0 | 45 | 0.9188 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 | | 0.9367 | 4.0 | 60 | 0.9105 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 | | 0.9426 | 5.0 | 75 | 0.8940 | 0.0361 | 0.0006 | 0.0169 | 0.0357 | 0.0502 | | 0.9326 | 6.0 | 90 | 0.8707 | 0.0800 | 0.0189 | 0.0462 | 0.0952 | 0.0884 | | 0.9114 | 7.0 | 105 | 0.8584 | 0.0965 | 0.0168 | 0.0464 | 0.1151 | 0.1104 | | 0.8773 | 8.0 | 120 | 0.8524 | 0.1004 | 0.0178 | 0.0470 | 0.1243 | 0.1104 | | 0.8673 | 9.0 | 135 | 0.8486 | 0.0932 | 0.0216 | 0.0481 | 0.1111 | 0.1044 | | 0.8738 | 10.0 | 150 | 0.8444 | 0.0924 | 0.0242 | 0.0484 | 0.1085 | 0.1044 | | 0.8685 | 11.0 | 165 | 0.8404 | 0.0936 | 0.0232 | 0.0485 | 0.1138 | 0.1024 | | 0.8798 | 12.0 | 180 | 0.8350 | 0.0929 | 0.0237 | 0.0486 | 0.1138 | 0.1004 | | 0.8548 | 13.0 | 195 | 0.8299 | 0.0951 | 0.0238 | 0.0495 | 0.1190 | 0.1004 | | 0.8387 | 14.0 | 210 | 0.8216 | 0.0953 | 0.0244 | 0.0508 | 0.1190 | 0.1004 | | 0.8486 | 15.0 | 225 | 0.8124 | 0.0967 | 0.0237 | 0.0526 | 0.1243 | 0.0984 | | 0.8587 | 16.0 | 240 | 0.8042 | 0.0952 | 0.0228 | 0.0517 | 0.1270 | 0.0924 | | 0.8377 | 17.0 | 255 | 0.7949 | 0.0968 | 0.0220 | 0.0520 | 0.1230 | 0.1004 | | 0.8159 | 18.0 | 270 | 0.7868 | 0.0951 | 0.0224 | 0.0538 | 0.1204 | 0.0984 | | 0.8246 | 19.0 | 285 | 0.7795 | 0.0975 | 0.0222 | 0.0538 | 0.1243 | 0.1004 | | 0.8126 | 20.0 | 300 | 0.7711 | 0.0982 | 0.0209 | 0.0536 | 0.1243 | 0.1024 | | 0.8009 | 21.0 | 315 | 0.7632 | 0.1001 | 0.0213 | 0.0538 | 0.1230 | 0.1084 | | 0.802 | 22.0 | 330 | 0.7608 | 0.0985 | 0.0182 | 0.0512 | 0.1164 | 0.1124 | | 0.7926 | 23.0 | 345 | 0.7598 | 0.0989 | 0.0171 | 0.0478 | 0.1124 | 0.1185 | | 0.7966 | 24.0 | 360 | 0.7571 | 0.1026 | 0.0167 | 0.0480 | 0.1177 | 0.1225 | | 0.8129 | 25.0 | 375 | 0.7538 | 0.1021 | 0.0173 | 0.0481 | 0.1164 | 0.1225 | | 0.7831 | 26.0 | 390 | 0.7509 | 0.1029 | 0.0152 | 0.0451 | 0.1217 | 0.1205 | | 0.7765 | 27.0 | 405 | 0.7482 | 0.0992 | 0.0141 | 0.0437 | 0.1190 | 0.1145 | | 0.7814 | 28.0 | 420 | 0.7449 | 0.1040 | 0.0142 | 0.0436 | 0.1270 | 0.1185 | | 0.7663 | 29.0 | 435 | 0.7426 | 0.1040 | 0.0142 | 0.0436 | 0.1270 | 0.1185 | | 0.7641 | 30.0 | 450 | 0.7402 | 0.1043 | 0.0135 | 0.0393 | 0.1230 | 0.1245 | | 0.768 | 31.0 | 465 | 0.7388 | 0.1053 | 0.0144 | 0.0408 | 0.1230 | 0.1265 | | 0.7629 | 32.0 | 480 | 0.7372 | 0.1043 | 0.0144 | 0.0408 | 0.1204 | 0.1265 | | 0.7536 | 33.0 | 495 | 0.7356 | 0.1101 | 0.0161 | 0.0471 | 0.1270 | 0.1325 | | 0.7709 | 34.0 | 510 | 0.7342 | 0.1094 | 0.0166 | 0.0475 | 0.1270 | 0.1305 | | 0.7521 | 35.0 | 525 | 0.7330 | 0.1092 | 0.0170 | 0.0476 | 0.1243 | 0.1325 | | 0.7741 | 36.0 | 540 | 0.7316 | 0.1074 | 0.0171 | 0.0476 | 0.1217 | 0.1305 | | 0.7614 | 37.0 | 555 | 0.7313 | 0.1087 | 0.0171 | 0.0476 | 0.1230 | 0.1325 | | 0.7663 | 38.0 | 570 | 0.7307 | 0.1079 | 0.0173 | 0.0476 | 0.1230 | 0.1305 | | 0.7562 | 39.0 | 585 | 0.7296 | 0.1079 | 0.0173 | 0.0476 | 0.1230 | 0.1305 | | 0.7706 | 40.0 | 600 | 0.7292 | 0.1079 | 0.0173 | 0.0476 | 0.1230 | 0.1305 | | 0.7512 | 41.0 | 615 | 0.7291 | 0.1079 | 0.0173 | 0.0476 | 0.1230 | 0.1305 | | 0.7469 | 42.0 | 630 | 0.7288 | 0.1085 | 0.0178 | 0.0481 | 0.1243 | 0.1305 | | 0.7544 | 43.0 | 645 | 0.7285 | 0.1081 | 0.0177 | 0.0466 | 0.1217 | 0.1325 | | 0.7639 | 44.0 | 660 | 0.7279 | 0.1092 | 0.0179 | 0.0466 | 0.1243 | 0.1325 | | 0.7505 | 45.0 | 675 | 0.7273 | 0.1120 | 0.0212 | 0.0528 | 0.1270 | 0.1345 | | 0.7491 | 46.0 | 690 | 0.7265 | 0.1120 | 0.0212 | 0.0528 | 0.1270 | 0.1345 | | 0.7525 | 47.0 | 705 | 0.7264 | 0.1087 | 0.0209 | 0.0522 | 0.1230 | 0.1305 | | 0.7535 | 48.0 | 720 | 0.7262 | 0.1114 | 0.0205 | 0.0523 | 0.1257 | 0.1345 | | 0.7596 | 49.0 | 735 | 0.7256 | 0.1124 | 0.0207 | 0.0523 | 0.1283 | 0.1345 | | 0.7368 | 50.0 | 750 | 0.7253 | 0.1087 | 0.0209 | 0.0522 | 0.1230 | 0.1305 | | 0.7649 | 51.0 | 765 | 0.7251 | 0.1053 | 0.0197 | 0.0507 | 0.1190 | 0.1265 | | 0.7516 | 52.0 | 780 | 0.7248 | 0.1053 | 0.0197 | 0.0507 | 0.1190 | 0.1265 | | 0.7592 | 53.0 | 795 | 0.7246 | 0.1038 | 0.0197 | 0.0494 | 0.1138 | 0.1285 | | 0.7258 | 54.0 | 810 | 0.7240 | 0.1099 | 0.0202 | 0.0508 | 0.1204 | 0.1365 | | 0.7524 | 55.0 | 825 | 0.7239 | 0.1038 | 0.0197 | 0.0494 | 0.1138 | 0.1285 | | 0.7534 | 56.0 | 840 | 0.7237 | 0.0970 | 0.0162 | 0.0411 | 0.1058 | 0.1225 | | 0.7583 | 57.0 | 855 | 0.7233 | 0.0968 | 0.0164 | 0.0411 | 0.1032 | 0.1245 | | 0.7468 | 58.0 | 870 | 0.7232 | 0.0970 | 0.0162 | 0.0411 | 0.1058 | 0.1225 | | 0.7567 | 59.0 | 885 | 0.7232 | 0.0970 | 0.0162 | 0.0411 | 0.1058 | 0.1225 | | 0.7433 | 60.0 | 900 | 0.7232 | 0.0970 | 0.0162 | 0.0411 | 0.1058 | 0.1225 | | 0.7569 | 61.0 | 915 | 0.7231 | 0.0971 | 0.0163 | 0.0411 | 0.1058 | 0.1225 | | 0.747 | 62.0 | 930 | 0.7230 | 0.0971 | 0.0163 | 0.0411 | 0.1058 | 0.1225 | | 0.7482 | 63.0 | 945 | 0.7230 | 0.0971 | 0.0163 | 0.0411 | 0.1058 | 0.1225 | | 0.7471 | 64.0 | 960 | 0.7230 | 0.0971 | 0.0163 | 0.0411 | 0.1058 | 0.1225 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1 - Datasets 2.14.4 - Tokenizers 0.13.3