codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_3
This model is a fine-tuned version of Salesforce/codet5p-770m-py on the mbpp dataset. It achieves the following results on the evaluation set:
- Loss: 0.7091
- Codebleu: 0.1023
- Ngram Match Score: 0.0222
- Weighted Ngram Match Score: 0.0462
- Syntax Match Score: 0.1283
- Dataflow Match Score: 0.1104
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 |
---|---|---|---|---|---|---|---|---|
0.979 | 1.0 | 15 | 0.9239 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 |
0.9649 | 2.0 | 30 | 0.9204 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 |
0.9697 | 3.0 | 45 | 0.9124 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 |
0.9338 | 4.0 | 60 | 0.8964 | 0.0297 | 0.0001 | 0.0144 | 0.0265 | 0.0442 |
0.9264 | 5.0 | 75 | 0.8709 | 0.0792 | 0.0099 | 0.0320 | 0.0992 | 0.0884 |
0.9012 | 6.0 | 90 | 0.8547 | 0.0910 | 0.0208 | 0.0490 | 0.1177 | 0.0924 |
0.8802 | 7.0 | 105 | 0.8462 | 0.0971 | 0.0231 | 0.0516 | 0.1217 | 0.1024 |
0.854 | 8.0 | 120 | 0.8402 | 0.1020 | 0.0237 | 0.0524 | 0.1296 | 0.1064 |
0.8453 | 9.0 | 135 | 0.8336 | 0.1031 | 0.0236 | 0.0524 | 0.1323 | 0.1064 |
0.8498 | 10.0 | 150 | 0.8244 | 0.1044 | 0.0222 | 0.0511 | 0.1323 | 0.1104 |
0.841 | 11.0 | 165 | 0.8126 | 0.1034 | 0.0223 | 0.0511 | 0.1296 | 0.1104 |
0.8499 | 12.0 | 180 | 0.7990 | 0.1016 | 0.0229 | 0.0513 | 0.1270 | 0.1084 |
0.8231 | 13.0 | 195 | 0.7866 | 0.1010 | 0.0173 | 0.0399 | 0.1257 | 0.1124 |
0.8041 | 14.0 | 210 | 0.7748 | 0.1051 | 0.0197 | 0.0468 | 0.1336 | 0.1124 |
0.8148 | 15.0 | 225 | 0.7668 | 0.1014 | 0.0184 | 0.0459 | 0.1270 | 0.1104 |
0.8247 | 16.0 | 240 | 0.7604 | 0.1028 | 0.0168 | 0.0433 | 0.1336 | 0.1084 |
0.802 | 17.0 | 255 | 0.7562 | 0.1020 | 0.0164 | 0.0433 | 0.1336 | 0.1064 |
0.7836 | 18.0 | 270 | 0.7522 | 0.1086 | 0.0147 | 0.0422 | 0.1468 | 0.1104 |
0.798 | 19.0 | 285 | 0.7491 | 0.1086 | 0.0144 | 0.0424 | 0.1468 | 0.1104 |
0.7846 | 20.0 | 300 | 0.7465 | 0.1086 | 0.0146 | 0.0424 | 0.1468 | 0.1104 |
0.7735 | 21.0 | 315 | 0.7436 | 0.1086 | 0.0146 | 0.0424 | 0.1468 | 0.1104 |
0.7776 | 22.0 | 330 | 0.7416 | 0.1037 | 0.0179 | 0.0512 | 0.1296 | 0.1124 |
0.7719 | 23.0 | 345 | 0.7408 | 0.1043 | 0.0177 | 0.0512 | 0.1310 | 0.1124 |
0.7793 | 24.0 | 360 | 0.7388 | 0.0965 | 0.0129 | 0.0369 | 0.1204 | 0.1084 |
0.7989 | 25.0 | 375 | 0.7364 | 0.1041 | 0.0198 | 0.0530 | 0.1296 | 0.1124 |
0.7667 | 26.0 | 390 | 0.7341 | 0.0966 | 0.0160 | 0.0424 | 0.1164 | 0.1104 |
0.7536 | 27.0 | 405 | 0.7327 | 0.0967 | 0.0161 | 0.0439 | 0.1164 | 0.1104 |
0.7697 | 28.0 | 420 | 0.7306 | 0.0987 | 0.0170 | 0.0439 | 0.1190 | 0.1124 |
0.75 | 29.0 | 435 | 0.7288 | 0.0987 | 0.0170 | 0.0439 | 0.1190 | 0.1124 |
0.7497 | 30.0 | 450 | 0.7264 | 0.0977 | 0.0168 | 0.0424 | 0.1190 | 0.1104 |
0.7509 | 31.0 | 465 | 0.7247 | 0.1024 | 0.0201 | 0.0511 | 0.1257 | 0.1124 |
0.7486 | 32.0 | 480 | 0.7229 | 0.0982 | 0.0165 | 0.0424 | 0.1204 | 0.1104 |
0.7383 | 33.0 | 495 | 0.7214 | 0.0976 | 0.0162 | 0.0424 | 0.1230 | 0.1064 |
0.7624 | 34.0 | 510 | 0.7201 | 0.0982 | 0.0165 | 0.0422 | 0.1204 | 0.1104 |
0.7411 | 35.0 | 525 | 0.7189 | 0.0985 | 0.0169 | 0.0422 | 0.1230 | 0.1084 |
0.7633 | 36.0 | 540 | 0.7179 | 0.0985 | 0.0170 | 0.0422 | 0.1230 | 0.1084 |
0.7446 | 37.0 | 555 | 0.7171 | 0.1065 | 0.0171 | 0.0426 | 0.1389 | 0.1124 |
0.7541 | 38.0 | 570 | 0.7164 | 0.1067 | 0.0179 | 0.0439 | 0.1389 | 0.1124 |
0.7427 | 39.0 | 585 | 0.7154 | 0.1084 | 0.0181 | 0.0423 | 0.1455 | 0.1104 |
0.7573 | 40.0 | 600 | 0.7150 | 0.1062 | 0.0161 | 0.0384 | 0.1415 | 0.1104 |
0.7374 | 41.0 | 615 | 0.7145 | 0.1062 | 0.0161 | 0.0384 | 0.1415 | 0.1104 |
0.7351 | 42.0 | 630 | 0.7138 | 0.1094 | 0.0178 | 0.0423 | 0.1481 | 0.1104 |
0.7417 | 43.0 | 645 | 0.7133 | 0.1023 | 0.0172 | 0.0427 | 0.1323 | 0.1084 |
0.7491 | 44.0 | 660 | 0.7130 | 0.0994 | 0.0172 | 0.0428 | 0.1270 | 0.1064 |
0.742 | 45.0 | 675 | 0.7125 | 0.1010 | 0.0175 | 0.0428 | 0.1270 | 0.1104 |
0.7327 | 46.0 | 690 | 0.7122 | 0.1113 | 0.0157 | 0.0384 | 0.1442 | 0.1205 |
0.7417 | 47.0 | 705 | 0.7120 | 0.1005 | 0.0159 | 0.0389 | 0.1230 | 0.1145 |
0.7406 | 48.0 | 720 | 0.7120 | 0.1019 | 0.0183 | 0.0427 | 0.1270 | 0.1124 |
0.743 | 49.0 | 735 | 0.7115 | 0.1060 | 0.0191 | 0.0433 | 0.1349 | 0.1145 |
0.7224 | 50.0 | 750 | 0.7110 | 0.0997 | 0.0159 | 0.0389 | 0.1230 | 0.1124 |
0.7583 | 51.0 | 765 | 0.7106 | 0.0997 | 0.0159 | 0.0389 | 0.1230 | 0.1124 |
0.7425 | 52.0 | 780 | 0.7104 | 0.1001 | 0.0173 | 0.0395 | 0.1257 | 0.1104 |
0.7446 | 53.0 | 795 | 0.7101 | 0.1022 | 0.0213 | 0.0458 | 0.1283 | 0.1104 |
0.7119 | 54.0 | 810 | 0.7100 | 0.1027 | 0.0212 | 0.0458 | 0.1296 | 0.1104 |
0.7382 | 55.0 | 825 | 0.7098 | 0.1027 | 0.0212 | 0.0458 | 0.1296 | 0.1104 |
0.7391 | 56.0 | 840 | 0.7097 | 0.1027 | 0.0212 | 0.0458 | 0.1296 | 0.1104 |
0.7498 | 57.0 | 855 | 0.7095 | 0.1028 | 0.0218 | 0.0463 | 0.1296 | 0.1104 |
0.7313 | 58.0 | 870 | 0.7094 | 0.1028 | 0.0218 | 0.0463 | 0.1296 | 0.1104 |
0.7456 | 59.0 | 885 | 0.7092 | 0.1028 | 0.0218 | 0.0463 | 0.1296 | 0.1104 |
0.7291 | 60.0 | 900 | 0.7092 | 0.1028 | 0.0218 | 0.0463 | 0.1296 | 0.1104 |
0.7467 | 61.0 | 915 | 0.7092 | 0.1028 | 0.0218 | 0.0463 | 0.1296 | 0.1104 |
0.7353 | 62.0 | 930 | 0.7091 | 0.1023 | 0.0222 | 0.0462 | 0.1283 | 0.1104 |
0.7365 | 63.0 | 945 | 0.7091 | 0.1023 | 0.0222 | 0.0462 | 0.1283 | 0.1104 |
0.7277 | 64.0 | 960 | 0.7091 | 0.1023 | 0.0222 | 0.0462 | 0.1283 | 0.1104 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
Model tree for vichyt/codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_3
Base model
Salesforce/codet5p-770m-py
Finetuned
this model