--- 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_13 results: [] library_name: peft --- # codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_13 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: 0.7334 - Codebleu: 0.1044 - Ngram Match Score: 0.0286 - Weighted Ngram Match Score: 0.0569 - Syntax Match Score: 0.1151 - Dataflow Match Score: 0.1245 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:| | 0.9803 | 1.0 | 15 | 0.9245 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9641 | 2.0 | 30 | 0.9232 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9775 | 3.0 | 45 | 0.9200 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9449 | 4.0 | 60 | 0.9133 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 | | 0.9539 | 5.0 | 75 | 0.8999 | 0.0208 | 0.0000 | 0.0052 | 0.0185 | 0.0321 | | 0.9449 | 6.0 | 90 | 0.8759 | 0.0610 | 0.0024 | 0.0276 | 0.0728 | 0.0723 | | 0.925 | 7.0 | 105 | 0.8504 | 0.0977 | 0.0175 | 0.0469 | 0.1177 | 0.1104 | | 0.8704 | 8.0 | 120 | 0.8351 | 0.0965 | 0.0217 | 0.0526 | 0.1204 | 0.1024 | | 0.8526 | 9.0 | 135 | 0.8225 | 0.1007 | 0.0203 | 0.0501 | 0.1217 | 0.1124 | | 0.8472 | 10.0 | 150 | 0.8102 | 0.1003 | 0.0191 | 0.0494 | 0.1190 | 0.1145 | | 0.8314 | 11.0 | 165 | 0.7986 | 0.1002 | 0.0128 | 0.0360 | 0.1177 | 0.1205 | | 0.8245 | 12.0 | 180 | 0.7881 | 0.1006 | 0.0120 | 0.0359 | 0.1270 | 0.1124 | | 0.8023 | 13.0 | 195 | 0.7798 | 0.1025 | 0.0134 | 0.0406 | 0.1204 | 0.1225 | | 0.7823 | 14.0 | 210 | 0.7727 | 0.1074 | 0.0141 | 0.0408 | 0.1283 | 0.1265 | | 0.7897 | 15.0 | 225 | 0.7666 | 0.1109 | 0.0150 | 0.0404 | 0.1349 | 0.1285 | | 0.7949 | 16.0 | 240 | 0.7638 | 0.1055 | 0.0147 | 0.0389 | 0.1177 | 0.1325 | | 0.7817 | 17.0 | 255 | 0.7608 | 0.1062 | 0.0150 | 0.0407 | 0.1230 | 0.1285 | | 0.7543 | 18.0 | 270 | 0.7588 | 0.1083 | 0.0147 | 0.0411 | 0.1323 | 0.1245 | | 0.7681 | 19.0 | 285 | 0.7561 | 0.1083 | 0.0147 | 0.0411 | 0.1323 | 0.1245 | | 0.751 | 20.0 | 300 | 0.7541 | 0.1111 | 0.0178 | 0.0473 | 0.1349 | 0.1265 | | 0.7454 | 21.0 | 315 | 0.7517 | 0.1019 | 0.0151 | 0.0406 | 0.1164 | 0.1245 | | 0.7345 | 22.0 | 330 | 0.7495 | 0.1047 | 0.0183 | 0.0469 | 0.1190 | 0.1265 | | 0.7333 | 23.0 | 345 | 0.7488 | 0.1128 | 0.0188 | 0.0470 | 0.1349 | 0.1305 | | 0.7369 | 24.0 | 360 | 0.7477 | 0.1136 | 0.0236 | 0.0558 | 0.1296 | 0.1345 | | 0.758 | 25.0 | 375 | 0.7462 | 0.1189 | 0.0209 | 0.0504 | 0.1468 | 0.1325 | | 0.7269 | 26.0 | 390 | 0.7454 | 0.1166 | 0.0253 | 0.0580 | 0.1362 | 0.1345 | | 0.7167 | 27.0 | 405 | 0.7433 | 0.1165 | 0.0265 | 0.0582 | 0.1336 | 0.1365 | | 0.7174 | 28.0 | 420 | 0.7424 | 0.1156 | 0.0260 | 0.0576 | 0.1336 | 0.1345 | | 0.7099 | 29.0 | 435 | 0.7424 | 0.1190 | 0.0259 | 0.0574 | 0.1442 | 0.1325 | | 0.7066 | 30.0 | 450 | 0.7420 | 0.1127 | 0.0277 | 0.0581 | 0.1257 | 0.1345 | | 0.7054 | 31.0 | 465 | 0.7413 | 0.1111 | 0.0280 | 0.0583 | 0.1257 | 0.1305 | | 0.7067 | 32.0 | 480 | 0.7404 | 0.1111 | 0.0283 | 0.0583 | 0.1257 | 0.1305 | | 0.6996 | 33.0 | 495 | 0.7400 | 0.1090 | 0.0283 | 0.0582 | 0.1243 | 0.1265 | | 0.7066 | 34.0 | 510 | 0.7386 | 0.1088 | 0.0274 | 0.0575 | 0.1243 | 0.1265 | | 0.6848 | 35.0 | 525 | 0.7382 | 0.1081 | 0.0278 | 0.0575 | 0.1243 | 0.1245 | | 0.7107 | 36.0 | 540 | 0.7381 | 0.1046 | 0.0275 | 0.0573 | 0.1177 | 0.1225 | | 0.7004 | 37.0 | 555 | 0.7381 | 0.1053 | 0.0290 | 0.0579 | 0.1151 | 0.1265 | | 0.699 | 38.0 | 570 | 0.7382 | 0.1067 | 0.0290 | 0.0579 | 0.1124 | 0.1325 | | 0.6935 | 39.0 | 585 | 0.7370 | 0.1067 | 0.0290 | 0.0579 | 0.1124 | 0.1325 | | 0.7007 | 40.0 | 600 | 0.7361 | 0.1061 | 0.0287 | 0.0579 | 0.1151 | 0.1285 | | 0.6844 | 41.0 | 615 | 0.7359 | 0.1053 | 0.0287 | 0.0579 | 0.1151 | 0.1265 | | 0.682 | 42.0 | 630 | 0.7353 | 0.1051 | 0.0293 | 0.0579 | 0.1124 | 0.1285 | | 0.682 | 43.0 | 645 | 0.7352 | 0.1053 | 0.0287 | 0.0579 | 0.1151 | 0.1265 | | 0.6876 | 44.0 | 660 | 0.7349 | 0.1053 | 0.0291 | 0.0576 | 0.1151 | 0.1265 | | 0.6861 | 45.0 | 675 | 0.7350 | 0.1059 | 0.0294 | 0.0576 | 0.1124 | 0.1305 | | 0.6762 | 46.0 | 690 | 0.7351 | 0.1053 | 0.0291 | 0.0576 | 0.1151 | 0.1265 | | 0.6879 | 47.0 | 705 | 0.7348 | 0.1035 | 0.0283 | 0.0569 | 0.1151 | 0.1225 | | 0.6832 | 48.0 | 720 | 0.7349 | 0.1035 | 0.0283 | 0.0569 | 0.1151 | 0.1225 | | 0.6796 | 49.0 | 735 | 0.7346 | 0.1053 | 0.0291 | 0.0576 | 0.1151 | 0.1265 | | 0.6752 | 50.0 | 750 | 0.7347 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6965 | 51.0 | 765 | 0.7347 | 0.1035 | 0.0283 | 0.0569 | 0.1151 | 0.1225 | | 0.6912 | 52.0 | 780 | 0.7344 | 0.1035 | 0.0283 | 0.0569 | 0.1151 | 0.1225 | | 0.6869 | 53.0 | 795 | 0.7341 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6584 | 54.0 | 810 | 0.7339 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6775 | 55.0 | 825 | 0.7337 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6832 | 56.0 | 840 | 0.7338 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6834 | 57.0 | 855 | 0.7338 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.671 | 58.0 | 870 | 0.7336 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6883 | 59.0 | 885 | 0.7335 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6665 | 60.0 | 900 | 0.7334 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6824 | 61.0 | 915 | 0.7335 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6749 | 62.0 | 930 | 0.7334 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6758 | 63.0 | 945 | 0.7334 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | | 0.6646 | 64.0 | 960 | 0.7334 | 0.1044 | 0.0286 | 0.0569 | 0.1151 | 0.1245 | ### Framework versions - PEFT 0.4.0 - Transformers 4.31.0 - Pytorch 2.0.1 - Datasets 2.14.4 - Tokenizers 0.13.3