--- 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_20 results: [] --- # codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_20 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: 0.7097 - Codebleu: 0.1179 - Ngram Match Score: 0.0320 - Weighted Ngram Match Score: 0.0611 - Syntax Match Score: 0.1310 - Dataflow Match Score: 0.1406 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:| | 0.9712 | 1.0 | 15 | 0.9246 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.961 | 2.0 | 30 | 0.9235 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9738 | 3.0 | 45 | 0.9209 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 | | 0.9419 | 4.0 | 60 | 0.9152 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 | | 0.9577 | 5.0 | 75 | 0.9032 | 0.0096 | 0.0000 | 0.0002 | 0.0079 | 0.0161 | | 0.9445 | 6.0 | 90 | 0.8821 | 0.0442 | 0.0008 | 0.0261 | 0.0437 | 0.0602 | | 0.9365 | 7.0 | 105 | 0.8541 | 0.0902 | 0.0137 | 0.0421 | 0.1111 | 0.1004 | | 0.8813 | 8.0 | 120 | 0.8311 | 0.1028 | 0.0219 | 0.0518 | 0.1323 | 0.1064 | | 0.8601 | 9.0 | 135 | 0.8123 | 0.1046 | 0.0210 | 0.0491 | 0.1336 | 0.1104 | | 0.8338 | 10.0 | 150 | 0.7944 | 0.1056 | 0.0186 | 0.0480 | 0.1310 | 0.1165 | | 0.8059 | 11.0 | 165 | 0.7796 | 0.1008 | 0.0145 | 0.0380 | 0.1164 | 0.1225 | | 0.7975 | 12.0 | 180 | 0.7691 | 0.1015 | 0.0131 | 0.0357 | 0.1190 | 0.1225 | | 0.7782 | 13.0 | 195 | 0.7633 | 0.1020 | 0.0116 | 0.0341 | 0.1230 | 0.1205 | | 0.7598 | 14.0 | 210 | 0.7581 | 0.1006 | 0.0126 | 0.0352 | 0.1230 | 0.1165 | | 0.7752 | 15.0 | 225 | 0.7533 | 0.0998 | 0.0118 | 0.0332 | 0.1177 | 0.1205 | | 0.7779 | 16.0 | 240 | 0.7498 | 0.0977 | 0.0124 | 0.0332 | 0.1124 | 0.1205 | | 0.7616 | 17.0 | 255 | 0.7468 | 0.1035 | 0.0163 | 0.0423 | 0.1177 | 0.1265 | | 0.746 | 18.0 | 270 | 0.7444 | 0.1044 | 0.0163 | 0.0423 | 0.1177 | 0.1285 | | 0.7526 | 19.0 | 285 | 0.7416 | 0.1030 | 0.0174 | 0.0438 | 0.1177 | 0.1245 | | 0.7435 | 20.0 | 300 | 0.7395 | 0.1043 | 0.0208 | 0.0501 | 0.1164 | 0.1265 | | 0.7304 | 21.0 | 315 | 0.7371 | 0.1133 | 0.0223 | 0.0513 | 0.1283 | 0.1365 | | 0.7321 | 22.0 | 330 | 0.7346 | 0.1195 | 0.0290 | 0.0593 | 0.1362 | 0.1406 | | 0.7297 | 23.0 | 345 | 0.7337 | 0.1158 | 0.0245 | 0.0526 | 0.1336 | 0.1365 | | 0.7299 | 24.0 | 360 | 0.7322 | 0.1174 | 0.0245 | 0.0528 | 0.1336 | 0.1406 | | 0.7459 | 25.0 | 375 | 0.7306 | 0.1100 | 0.0238 | 0.0511 | 0.1257 | 0.1305 | | 0.7243 | 26.0 | 390 | 0.7290 | 0.1155 | 0.0289 | 0.0584 | 0.1283 | 0.1386 | | 0.7126 | 27.0 | 405 | 0.7276 | 0.1155 | 0.0289 | 0.0584 | 0.1283 | 0.1386 | | 0.723 | 28.0 | 420 | 0.7264 | 0.1120 | 0.0261 | 0.0529 | 0.1257 | 0.1345 | | 0.7073 | 29.0 | 435 | 0.7252 | 0.1155 | 0.0294 | 0.0584 | 0.1283 | 0.1386 | | 0.7099 | 30.0 | 450 | 0.7239 | 0.1179 | 0.0309 | 0.0620 | 0.1310 | 0.1406 | | 0.7062 | 31.0 | 465 | 0.7233 | 0.1176 | 0.0301 | 0.0603 | 0.1310 | 0.1406 | | 0.6998 | 32.0 | 480 | 0.7227 | 0.1261 | 0.0353 | 0.0705 | 0.1362 | 0.1526 | | 0.706 | 33.0 | 495 | 0.7221 | 0.1249 | 0.0360 | 0.0706 | 0.1349 | 0.1506 | | 0.7079 | 34.0 | 510 | 0.7205 | 0.1249 | 0.0360 | 0.0706 | 0.1349 | 0.1506 | | 0.6911 | 35.0 | 525 | 0.7198 | 0.1248 | 0.0357 | 0.0702 | 0.1349 | 0.1506 | | 0.7166 | 36.0 | 540 | 0.7193 | 0.1248 | 0.0357 | 0.0702 | 0.1349 | 0.1506 | | 0.7007 | 37.0 | 555 | 0.7186 | 0.1248 | 0.0357 | 0.0702 | 0.1349 | 0.1506 | | 0.7063 | 38.0 | 570 | 0.7181 | 0.1248 | 0.0357 | 0.0702 | 0.1349 | 0.1506 | | 0.6969 | 39.0 | 585 | 0.7169 | 0.1248 | 0.0357 | 0.0702 | 0.1349 | 0.1506 | | 0.7031 | 40.0 | 600 | 0.7163 | 0.1248 | 0.0361 | 0.0702 | 0.1349 | 0.1506 | | 0.6894 | 41.0 | 615 | 0.7159 | 0.1248 | 0.0361 | 0.0702 | 0.1349 | 0.1506 | | 0.6873 | 42.0 | 630 | 0.7151 | 0.1220 | 0.0326 | 0.0643 | 0.1323 | 0.1486 | | 0.6869 | 43.0 | 645 | 0.7145 | 0.1213 | 0.0334 | 0.0645 | 0.1323 | 0.1466 | | 0.6923 | 44.0 | 660 | 0.7141 | 0.1214 | 0.0339 | 0.0645 | 0.1323 | 0.1466 | | 0.6854 | 45.0 | 675 | 0.7135 | 0.1165 | 0.0325 | 0.0629 | 0.1310 | 0.1365 | | 0.6829 | 46.0 | 690 | 0.7132 | 0.1166 | 0.0330 | 0.0629 | 0.1310 | 0.1365 | | 0.6896 | 47.0 | 705 | 0.7128 | 0.1163 | 0.0318 | 0.0611 | 0.1310 | 0.1365 | | 0.6915 | 48.0 | 720 | 0.7126 | 0.1163 | 0.0320 | 0.0611 | 0.1310 | 0.1365 | | 0.6888 | 49.0 | 735 | 0.7124 | 0.1163 | 0.0320 | 0.0611 | 0.1310 | 0.1365 | | 0.6814 | 50.0 | 750 | 0.7122 | 0.1163 | 0.0320 | 0.0611 | 0.1310 | 0.1365 | | 0.7024 | 51.0 | 765 | 0.7117 | 0.1166 | 0.0332 | 0.0629 | 0.1310 | 0.1365 | | 0.6981 | 52.0 | 780 | 0.7112 | 0.1166 | 0.0332 | 0.0629 | 0.1310 | 0.1365 | | 0.6924 | 53.0 | 795 | 0.7108 | 0.1166 | 0.0332 | 0.0629 | 0.1310 | 0.1365 | | 0.6653 | 54.0 | 810 | 0.7106 | 0.1166 | 0.0332 | 0.0629 | 0.1310 | 0.1365 | | 0.6821 | 55.0 | 825 | 0.7103 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6872 | 56.0 | 840 | 0.7103 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6866 | 57.0 | 855 | 0.7103 | 0.1182 | 0.0332 | 0.0629 | 0.1310 | 0.1406 | | 0.6844 | 58.0 | 870 | 0.7102 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6981 | 59.0 | 885 | 0.7100 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6778 | 60.0 | 900 | 0.7099 | 0.1182 | 0.0332 | 0.0629 | 0.1310 | 0.1406 | | 0.6896 | 61.0 | 915 | 0.7098 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6791 | 62.0 | 930 | 0.7098 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6803 | 63.0 | 945 | 0.7097 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | | 0.6745 | 64.0 | 960 | 0.7097 | 0.1179 | 0.0320 | 0.0611 | 0.1310 | 0.1406 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1 - Datasets 2.14.4 - Tokenizers 0.13.3