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---
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_0_1_2_3
results: []
---
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# codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_0_1_2_3
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: 0.6901
- Codebleu: 0.1306
- Ngram Match Score: 0.0314
- Weighted Ngram Match Score: 0.0585
- Syntax Match Score: 0.1495
- Dataflow Match Score: 0.1546
## 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: 128
### Training results
| Training Loss | Epoch | Step | Validation Loss | Codebleu | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|
| 0.9882 | 1.0 | 15 | 0.9229 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 |
| 0.9681 | 2.0 | 30 | 0.9160 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 |
| 0.9554 | 3.0 | 45 | 0.9006 | 0.0268 | 0.0000 | 0.0124 | 0.0238 | 0.0402 |
| 0.915 | 4.0 | 60 | 0.8736 | 0.0695 | 0.0115 | 0.0398 | 0.0807 | 0.0803 |
| 0.9066 | 5.0 | 75 | 0.8538 | 0.1023 | 0.0185 | 0.0469 | 0.1230 | 0.1165 |
| 0.8751 | 6.0 | 90 | 0.8434 | 0.1016 | 0.0229 | 0.0510 | 0.1270 | 0.1084 |
| 0.8642 | 7.0 | 105 | 0.8340 | 0.0983 | 0.0235 | 0.0520 | 0.1243 | 0.1024 |
| 0.8505 | 8.0 | 120 | 0.8211 | 0.0983 | 0.0225 | 0.0510 | 0.1270 | 0.1004 |
| 0.8303 | 9.0 | 135 | 0.8097 | 0.0983 | 0.0225 | 0.0509 | 0.1270 | 0.1004 |
| 0.8254 | 10.0 | 150 | 0.7979 | 0.0983 | 0.0225 | 0.0509 | 0.1270 | 0.1004 |
| 0.8095 | 11.0 | 165 | 0.7858 | 0.1003 | 0.0231 | 0.0515 | 0.1296 | 0.1024 |
| 0.8128 | 12.0 | 180 | 0.7688 | 0.1047 | 0.0249 | 0.0563 | 0.1310 | 0.1104 |
| 0.7953 | 13.0 | 195 | 0.7534 | 0.0993 | 0.0179 | 0.0439 | 0.1243 | 0.1084 |
| 0.7708 | 14.0 | 210 | 0.7435 | 0.1013 | 0.0142 | 0.0415 | 0.1310 | 0.1084 |
| 0.7846 | 15.0 | 225 | 0.7371 | 0.0940 | 0.0131 | 0.0386 | 0.1177 | 0.1044 |
| 0.7883 | 16.0 | 240 | 0.7320 | 0.1034 | 0.0164 | 0.0470 | 0.1283 | 0.1145 |
| 0.7718 | 17.0 | 255 | 0.7240 | 0.1030 | 0.0170 | 0.0471 | 0.1270 | 0.1145 |
| 0.7582 | 18.0 | 270 | 0.7217 | 0.1117 | 0.0183 | 0.0502 | 0.1415 | 0.1205 |
| 0.7627 | 19.0 | 285 | 0.7189 | 0.1125 | 0.0207 | 0.0507 | 0.1429 | 0.1205 |
| 0.7534 | 20.0 | 300 | 0.7167 | 0.1118 | 0.0203 | 0.0492 | 0.1415 | 0.1205 |
| 0.7398 | 21.0 | 315 | 0.7131 | 0.1102 | 0.0190 | 0.0454 | 0.1389 | 0.1205 |
| 0.7323 | 22.0 | 330 | 0.7098 | 0.1231 | 0.0230 | 0.0540 | 0.1640 | 0.1245 |
| 0.728 | 23.0 | 345 | 0.7087 | 0.1137 | 0.0248 | 0.0538 | 0.1481 | 0.1165 |
| 0.7304 | 24.0 | 360 | 0.7074 | 0.1093 | 0.0237 | 0.0503 | 0.1402 | 0.1145 |
| 0.7446 | 25.0 | 375 | 0.7050 | 0.1109 | 0.0259 | 0.0537 | 0.1429 | 0.1145 |
| 0.7288 | 26.0 | 390 | 0.7040 | 0.1159 | 0.0284 | 0.0593 | 0.1534 | 0.1145 |
| 0.7069 | 27.0 | 405 | 0.7035 | 0.1259 | 0.0270 | 0.0591 | 0.1627 | 0.1305 |
| 0.7245 | 28.0 | 420 | 0.7022 | 0.1146 | 0.0281 | 0.0589 | 0.1442 | 0.1205 |
| 0.7008 | 29.0 | 435 | 0.7016 | 0.1211 | 0.0254 | 0.0527 | 0.1587 | 0.1245 |
| 0.701 | 30.0 | 450 | 0.7000 | 0.1138 | 0.0261 | 0.0532 | 0.1362 | 0.1285 |
| 0.7036 | 31.0 | 465 | 0.6982 | 0.1164 | 0.0278 | 0.0589 | 0.1468 | 0.1225 |
| 0.7003 | 32.0 | 480 | 0.6993 | 0.1159 | 0.0266 | 0.0547 | 0.1389 | 0.1305 |
| 0.7001 | 33.0 | 495 | 0.6992 | 0.1108 | 0.0268 | 0.0543 | 0.1362 | 0.1205 |
| 0.7008 | 34.0 | 510 | 0.6963 | 0.1104 | 0.0253 | 0.0519 | 0.1402 | 0.1165 |
| 0.6912 | 35.0 | 525 | 0.6961 | 0.1156 | 0.0249 | 0.0508 | 0.1376 | 0.1325 |
| 0.7156 | 36.0 | 540 | 0.6948 | 0.1142 | 0.0245 | 0.0508 | 0.1442 | 0.1225 |
| 0.6899 | 37.0 | 555 | 0.6961 | 0.1184 | 0.0272 | 0.0548 | 0.1429 | 0.1325 |
| 0.6983 | 38.0 | 570 | 0.6957 | 0.1091 | 0.0249 | 0.0495 | 0.1257 | 0.1285 |
| 0.6847 | 39.0 | 585 | 0.6942 | 0.1107 | 0.0228 | 0.0488 | 0.1362 | 0.1225 |
| 0.6907 | 40.0 | 600 | 0.6957 | 0.1114 | 0.0252 | 0.0517 | 0.1389 | 0.1205 |
| 0.6764 | 41.0 | 615 | 0.6948 | 0.1075 | 0.0214 | 0.0476 | 0.1270 | 0.1245 |
| 0.6877 | 42.0 | 630 | 0.6940 | 0.1027 | 0.0229 | 0.0494 | 0.1323 | 0.1064 |
| 0.6734 | 43.0 | 645 | 0.6936 | 0.1093 | 0.0208 | 0.0452 | 0.1243 | 0.1325 |
| 0.6796 | 44.0 | 660 | 0.6941 | 0.1093 | 0.0208 | 0.0452 | 0.1243 | 0.1325 |
| 0.6731 | 45.0 | 675 | 0.6949 | 0.1095 | 0.0210 | 0.0460 | 0.1243 | 0.1325 |
| 0.6716 | 46.0 | 690 | 0.6946 | 0.1087 | 0.0205 | 0.0446 | 0.1230 | 0.1325 |
| 0.6767 | 47.0 | 705 | 0.6943 | 0.1046 | 0.0222 | 0.0447 | 0.1243 | 0.1205 |
| 0.6658 | 48.0 | 720 | 0.6947 | 0.1147 | 0.0219 | 0.0464 | 0.1270 | 0.1426 |
| 0.6796 | 49.0 | 735 | 0.6942 | 0.1169 | 0.0216 | 0.0453 | 0.1310 | 0.1446 |
| 0.656 | 50.0 | 750 | 0.6949 | 0.1081 | 0.0206 | 0.0465 | 0.1230 | 0.1305 |
| 0.6778 | 51.0 | 765 | 0.6926 | 0.1048 | 0.0205 | 0.0451 | 0.1190 | 0.1265 |
| 0.6734 | 52.0 | 780 | 0.6921 | 0.1057 | 0.0216 | 0.0451 | 0.1230 | 0.1245 |
| 0.6692 | 53.0 | 795 | 0.6915 | 0.1111 | 0.0218 | 0.0457 | 0.1323 | 0.1285 |
| 0.6452 | 54.0 | 810 | 0.6903 | 0.1083 | 0.0225 | 0.0468 | 0.1270 | 0.1265 |
| 0.6686 | 55.0 | 825 | 0.6899 | 0.1085 | 0.0205 | 0.0429 | 0.1270 | 0.1285 |
| 0.6654 | 56.0 | 840 | 0.6896 | 0.1102 | 0.0210 | 0.0429 | 0.1270 | 0.1325 |
| 0.6734 | 57.0 | 855 | 0.6887 | 0.1066 | 0.0202 | 0.0424 | 0.1204 | 0.1305 |
| 0.6567 | 58.0 | 870 | 0.6898 | 0.1135 | 0.0200 | 0.0423 | 0.1257 | 0.1426 |
| 0.6631 | 59.0 | 885 | 0.6915 | 0.1205 | 0.0230 | 0.0454 | 0.1296 | 0.1546 |
| 0.6507 | 60.0 | 900 | 0.6913 | 0.1205 | 0.0230 | 0.0454 | 0.1296 | 0.1546 |
| 0.6769 | 61.0 | 915 | 0.6929 | 0.1219 | 0.0238 | 0.0476 | 0.1323 | 0.1546 |
| 0.6527 | 62.0 | 930 | 0.6912 | 0.1160 | 0.0221 | 0.0437 | 0.1230 | 0.1506 |
| 0.6568 | 63.0 | 945 | 0.6892 | 0.1155 | 0.0205 | 0.0425 | 0.1243 | 0.1486 |
| 0.6496 | 64.0 | 960 | 0.6882 | 0.1161 | 0.0271 | 0.0557 | 0.1349 | 0.1345 |
| 0.6676 | 65.0 | 975 | 0.6888 | 0.1085 | 0.0203 | 0.0422 | 0.1190 | 0.1365 |
| 0.6529 | 66.0 | 990 | 0.6882 | 0.1057 | 0.0199 | 0.0417 | 0.1124 | 0.1365 |
| 0.6663 | 67.0 | 1005 | 0.6867 | 0.1124 | 0.0214 | 0.0453 | 0.1217 | 0.1426 |
| 0.6473 | 68.0 | 1020 | 0.6890 | 0.1213 | 0.0236 | 0.0472 | 0.1349 | 0.1506 |
| 0.6411 | 69.0 | 1035 | 0.6905 | 0.1187 | 0.0237 | 0.0476 | 0.1362 | 0.1426 |
| 0.6609 | 70.0 | 1050 | 0.6895 | 0.1224 | 0.0232 | 0.0456 | 0.1402 | 0.1486 |
| 0.6456 | 71.0 | 1065 | 0.6893 | 0.1107 | 0.0226 | 0.0462 | 0.1270 | 0.1325 |
| 0.6556 | 72.0 | 1080 | 0.6873 | 0.1090 | 0.0256 | 0.0525 | 0.1164 | 0.1365 |
| 0.6453 | 73.0 | 1095 | 0.6892 | 0.1140 | 0.0231 | 0.0470 | 0.1230 | 0.1446 |
| 0.6341 | 74.0 | 1110 | 0.6901 | 0.1272 | 0.0304 | 0.0568 | 0.1376 | 0.1586 |
| 0.6413 | 75.0 | 1125 | 0.6895 | 0.1272 | 0.0304 | 0.0568 | 0.1376 | 0.1586 |
| 0.6435 | 76.0 | 1140 | 0.6911 | 0.1298 | 0.0310 | 0.0583 | 0.1455 | 0.1566 |
| 0.6557 | 77.0 | 1155 | 0.6906 | 0.1276 | 0.0297 | 0.0566 | 0.1429 | 0.1546 |
| 0.6408 | 78.0 | 1170 | 0.6892 | 0.1206 | 0.0286 | 0.0561 | 0.1296 | 0.1506 |
| 0.6411 | 79.0 | 1185 | 0.6905 | 0.1284 | 0.0299 | 0.0566 | 0.1429 | 0.1566 |
| 0.6315 | 80.0 | 1200 | 0.6884 | 0.1289 | 0.0247 | 0.0478 | 0.1376 | 0.1667 |
| 0.6283 | 81.0 | 1215 | 0.6895 | 0.1256 | 0.0267 | 0.0495 | 0.1323 | 0.1627 |
| 0.635 | 82.0 | 1230 | 0.6902 | 0.1333 | 0.0255 | 0.0480 | 0.1481 | 0.1667 |
| 0.6487 | 83.0 | 1245 | 0.6921 | 0.1354 | 0.0263 | 0.0497 | 0.1508 | 0.1687 |
| 0.6452 | 84.0 | 1260 | 0.6900 | 0.1306 | 0.0261 | 0.0497 | 0.1429 | 0.1647 |
| 0.624 | 85.0 | 1275 | 0.6904 | 0.1274 | 0.0267 | 0.0495 | 0.1349 | 0.1647 |
| 0.6231 | 86.0 | 1290 | 0.6927 | 0.1266 | 0.0317 | 0.0603 | 0.1389 | 0.1546 |
| 0.6245 | 87.0 | 1305 | 0.6921 | 0.1250 | 0.0317 | 0.0603 | 0.1349 | 0.1546 |
| 0.6429 | 88.0 | 1320 | 0.6898 | 0.1315 | 0.0325 | 0.0610 | 0.1508 | 0.1546 |
| 0.6321 | 89.0 | 1335 | 0.6908 | 0.1291 | 0.0316 | 0.0585 | 0.1455 | 0.1546 |
| 0.6345 | 90.0 | 1350 | 0.6916 | 0.1325 | 0.0335 | 0.0623 | 0.1508 | 0.1566 |
| 0.6252 | 91.0 | 1365 | 0.6904 | 0.1324 | 0.0326 | 0.0613 | 0.1508 | 0.1566 |
| 0.6253 | 92.0 | 1380 | 0.6898 | 0.1324 | 0.0326 | 0.0613 | 0.1508 | 0.1566 |
| 0.6236 | 93.0 | 1395 | 0.6896 | 0.1327 | 0.0327 | 0.0592 | 0.1481 | 0.1606 |
| 0.6177 | 94.0 | 1410 | 0.6902 | 0.1303 | 0.0330 | 0.0592 | 0.1442 | 0.1586 |
| 0.6318 | 95.0 | 1425 | 0.6904 | 0.1332 | 0.0324 | 0.0590 | 0.1534 | 0.1566 |
| 0.6304 | 96.0 | 1440 | 0.6910 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6263 | 97.0 | 1455 | 0.6913 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.619 | 98.0 | 1470 | 0.6918 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6401 | 99.0 | 1485 | 0.6896 | 0.1384 | 0.0264 | 0.0502 | 0.1561 | 0.1707 |
| 0.6298 | 100.0 | 1500 | 0.6888 | 0.1333 | 0.0262 | 0.0500 | 0.1495 | 0.1647 |
| 0.6166 | 101.0 | 1515 | 0.6896 | 0.1299 | 0.0314 | 0.0588 | 0.1495 | 0.1526 |
| 0.6128 | 102.0 | 1530 | 0.6909 | 0.1307 | 0.0316 | 0.0587 | 0.1495 | 0.1546 |
| 0.637 | 103.0 | 1545 | 0.6912 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6248 | 104.0 | 1560 | 0.6903 | 0.1290 | 0.0309 | 0.0584 | 0.1495 | 0.1506 |
| 0.6193 | 105.0 | 1575 | 0.6919 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6282 | 106.0 | 1590 | 0.6912 | 0.1261 | 0.0315 | 0.0583 | 0.1481 | 0.1446 |
| 0.6339 | 107.0 | 1605 | 0.6905 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6138 | 108.0 | 1620 | 0.6920 | 0.1266 | 0.0321 | 0.0609 | 0.1508 | 0.1426 |
| 0.6248 | 109.0 | 1635 | 0.6914 | 0.1312 | 0.0320 | 0.0611 | 0.1521 | 0.1526 |
| 0.6256 | 110.0 | 1650 | 0.6912 | 0.1312 | 0.0317 | 0.0613 | 0.1521 | 0.1526 |
| 0.6209 | 111.0 | 1665 | 0.6901 | 0.1287 | 0.0314 | 0.0610 | 0.1481 | 0.1506 |
| 0.6147 | 112.0 | 1680 | 0.6901 | 0.1304 | 0.0319 | 0.0613 | 0.1521 | 0.1506 |
| 0.6073 | 113.0 | 1695 | 0.6902 | 0.1319 | 0.0318 | 0.0605 | 0.1521 | 0.1546 |
| 0.6247 | 114.0 | 1710 | 0.6899 | 0.1306 | 0.0316 | 0.0585 | 0.1495 | 0.1546 |
| 0.6238 | 115.0 | 1725 | 0.6900 | 0.1306 | 0.0316 | 0.0585 | 0.1495 | 0.1546 |
| 0.6143 | 116.0 | 1740 | 0.6898 | 0.1261 | 0.0316 | 0.0583 | 0.1481 | 0.1446 |
| 0.6135 | 117.0 | 1755 | 0.6900 | 0.1261 | 0.0316 | 0.0583 | 0.1481 | 0.1446 |
| 0.6199 | 118.0 | 1770 | 0.6902 | 0.1261 | 0.0316 | 0.0583 | 0.1481 | 0.1446 |
| 0.6235 | 119.0 | 1785 | 0.6905 | 0.1254 | 0.0321 | 0.0588 | 0.1481 | 0.1426 |
| 0.6092 | 120.0 | 1800 | 0.6908 | 0.1261 | 0.0316 | 0.0583 | 0.1481 | 0.1446 |
| 0.6164 | 121.0 | 1815 | 0.6904 | 0.1261 | 0.0315 | 0.0583 | 0.1481 | 0.1446 |
| 0.6225 | 122.0 | 1830 | 0.6902 | 0.1261 | 0.0315 | 0.0583 | 0.1481 | 0.1446 |
| 0.6312 | 123.0 | 1845 | 0.6899 | 0.1298 | 0.0311 | 0.0582 | 0.1495 | 0.1526 |
| 0.6158 | 124.0 | 1860 | 0.6901 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6186 | 125.0 | 1875 | 0.6902 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6129 | 126.0 | 1890 | 0.6901 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6152 | 127.0 | 1905 | 0.6901 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
| 0.6171 | 128.0 | 1920 | 0.6901 | 0.1306 | 0.0314 | 0.0585 | 0.1495 | 0.1546 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
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