generated_from_trainer dataset:mbpp base_model:Salesforce/codet5p-770m-py license:bsd-3-clause region:us
---
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_12
  results: []
---

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# codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_12

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: 0.7241
- Codebleu: 0.1012
- Ngram Match Score: 0.0160
- Weighted Ngram Match Score: 0.0377
- Syntax Match Score: 0.1190
- Dataflow Match Score: 0.1205

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|
| 0.9814        | 1.0   | 15   | 0.9245          | 0.0072   | 0.0000            | 0.0000                     | 0.0079             | 0.0100               |
| 0.9647        | 2.0   | 30   | 0.9229          | 0.0072   | 0.0000            | 0.0000                     | 0.0079             | 0.0100               |
| 0.9776        | 3.0   | 45   | 0.9192          | 0.0080   | 0.0000            | 0.0000                     | 0.0079             | 0.0120               |
| 0.9443        | 4.0   | 60   | 0.9110          | 0.0096   | 0.0000            | 0.0001                     | 0.0079             | 0.0161               |
| 0.9505        | 5.0   | 75   | 0.8952          | 0.0435   | 0.0013            | 0.0233                     | 0.0384             | 0.0643               |
| 0.9446        | 6.0   | 90   | 0.8734          | 0.0817   | 0.0171            | 0.0472                     | 0.1019             | 0.0863               |
| 0.9284        | 7.0   | 105  | 0.8552          | 0.1028   | 0.0242            | 0.0568                     | 0.1243             | 0.1124               |
| 0.8778        | 8.0   | 120  | 0.8396          | 0.0995   | 0.0220            | 0.0527                     | 0.1217             | 0.1084               |
| 0.8601        | 9.0   | 135  | 0.8259          | 0.0995   | 0.0225            | 0.0517                     | 0.1217             | 0.1084               |
| 0.8488        | 10.0  | 150  | 0.8142          | 0.1046   | 0.0201            | 0.0524                     | 0.1310             | 0.1124               |
| 0.8333        | 11.0  | 165  | 0.8030          | 0.1009   | 0.0131            | 0.0374                     | 0.1190             | 0.1205               |
| 0.8299        | 12.0  | 180  | 0.7918          | 0.0976   | 0.0127            | 0.0373                     | 0.1151             | 0.1165               |
| 0.8054        | 13.0  | 195  | 0.7822          | 0.0978   | 0.0114            | 0.0346                     | 0.1164             | 0.1165               |
| 0.7855        | 14.0  | 210  | 0.7741          | 0.0979   | 0.0130            | 0.0397                     | 0.1151             | 0.1165               |
| 0.791         | 15.0  | 225  | 0.7684          | 0.0976   | 0.0115            | 0.0352                     | 0.1138             | 0.1185               |
| 0.7967        | 16.0  | 240  | 0.7647          | 0.1065   | 0.0162            | 0.0448                     | 0.1204             | 0.1305               |
| 0.7852        | 17.0  | 255  | 0.7612          | 0.1046   | 0.0157            | 0.0448                     | 0.1177             | 0.1285               |
| 0.7548        | 18.0  | 270  | 0.7583          | 0.1054   | 0.0162            | 0.0448                     | 0.1177             | 0.1305               |
| 0.7693        | 19.0  | 285  | 0.7555          | 0.1120   | 0.0175            | 0.0453                     | 0.1257             | 0.1386               |
| 0.7576        | 20.0  | 300  | 0.7538          | 0.1054   | 0.0165            | 0.0449                     | 0.1217             | 0.1265               |
| 0.7445        | 21.0  | 315  | 0.7519          | 0.1058   | 0.0162            | 0.0410                     | 0.1177             | 0.1325               |
| 0.7425        | 22.0  | 330  | 0.7496          | 0.1058   | 0.0162            | 0.0410                     | 0.1177             | 0.1325               |
| 0.739         | 23.0  | 345  | 0.7486          | 0.1077   | 0.0162            | 0.0410                     | 0.1204             | 0.1345               |
| 0.7392        | 24.0  | 360  | 0.7470          | 0.1107   | 0.0169            | 0.0415                     | 0.1217             | 0.1406               |
| 0.7633        | 25.0  | 375  | 0.7464          | 0.1045   | 0.0166            | 0.0410                     | 0.1204             | 0.1265               |
| 0.7303        | 26.0  | 390  | 0.7449          | 0.1150   | 0.0201            | 0.0466                     | 0.1323             | 0.1386               |
| 0.7168        | 27.0  | 405  | 0.7440          | 0.1158   | 0.0212            | 0.0479                     | 0.1336             | 0.1386               |
| 0.7239        | 28.0  | 420  | 0.7435          | 0.1137   | 0.0239            | 0.0538                     | 0.1323             | 0.1325               |
| 0.7132        | 29.0  | 435  | 0.7432          | 0.1044   | 0.0157            | 0.0380                     | 0.1230             | 0.1245               |
| 0.709         | 30.0  | 450  | 0.7418          | 0.0992   | 0.0139            | 0.0334                     | 0.1138             | 0.1225               |
| 0.7067        | 31.0  | 465  | 0.7408          | 0.0969   | 0.0154            | 0.0380                     | 0.1164             | 0.1124               |
| 0.711         | 32.0  | 480  | 0.7394          | 0.1009   | 0.0179            | 0.0440                     | 0.1204             | 0.1165               |
| 0.6992        | 33.0  | 495  | 0.7377          | 0.1008   | 0.0203            | 0.0456                     | 0.1190             | 0.1165               |
| 0.7045        | 34.0  | 510  | 0.7361          | 0.1009   | 0.0179            | 0.0440                     | 0.1204             | 0.1165               |
| 0.6858        | 35.0  | 525  | 0.7359          | 0.1008   | 0.0203            | 0.0456                     | 0.1190             | 0.1165               |
| 0.7107        | 36.0  | 540  | 0.7340          | 0.0989   | 0.0203            | 0.0456                     | 0.1164             | 0.1145               |
| 0.7013        | 37.0  | 555  | 0.7324          | 0.0999   | 0.0198            | 0.0454                     | 0.1190             | 0.1145               |
| 0.7027        | 38.0  | 570  | 0.7323          | 0.0992   | 0.0203            | 0.0453                     | 0.1151             | 0.1165               |
| 0.6956        | 39.0  | 585  | 0.7313          | 0.1054   | 0.0199            | 0.0445                     | 0.1270             | 0.1205               |
| 0.6998        | 40.0  | 600  | 0.7309          | 0.1022   | 0.0193            | 0.0445                     | 0.1270             | 0.1124               |
| 0.6856        | 41.0  | 615  | 0.7304          | 0.1027   | 0.0197            | 0.0443                     | 0.1243             | 0.1165               |
| 0.682         | 42.0  | 630  | 0.7296          | 0.1038   | 0.0197            | 0.0443                     | 0.1270             | 0.1165               |
| 0.6819        | 43.0  | 645  | 0.7295          | 0.1027   | 0.0197            | 0.0443                     | 0.1243             | 0.1165               |
| 0.6897        | 44.0  | 660  | 0.7288          | 0.1053   | 0.0208            | 0.0449                     | 0.1243             | 0.1225               |
| 0.6863        | 45.0  | 675  | 0.7287          | 0.1053   | 0.0208            | 0.0449                     | 0.1243             | 0.1225               |
| 0.6794        | 46.0  | 690  | 0.7281          | 0.1053   | 0.0208            | 0.0449                     | 0.1243             | 0.1225               |
| 0.6907        | 47.0  | 705  | 0.7273          | 0.1053   | 0.0208            | 0.0453                     | 0.1243             | 0.1225               |
| 0.6838        | 48.0  | 720  | 0.7267          | 0.1053   | 0.0208            | 0.0453                     | 0.1243             | 0.1225               |
| 0.6848        | 49.0  | 735  | 0.7261          | 0.1024   | 0.0171            | 0.0386                     | 0.1217             | 0.1205               |
| 0.6712        | 50.0  | 750  | 0.7263          | 0.1024   | 0.0171            | 0.0386                     | 0.1217             | 0.1205               |
| 0.6962        | 51.0  | 765  | 0.7262          | 0.1024   | 0.0170            | 0.0388                     | 0.1217             | 0.1205               |
| 0.695         | 52.0  | 780  | 0.7257          | 0.1024   | 0.0170            | 0.0388                     | 0.1217             | 0.1205               |
| 0.6858        | 53.0  | 795  | 0.7254          | 0.1024   | 0.0170            | 0.0388                     | 0.1217             | 0.1205               |
| 0.6603        | 54.0  | 810  | 0.7252          | 0.1024   | 0.0170            | 0.0388                     | 0.1217             | 0.1205               |
| 0.6806        | 55.0  | 825  | 0.7252          | 0.1024   | 0.0170            | 0.0388                     | 0.1217             | 0.1205               |
| 0.683         | 56.0  | 840  | 0.7251          | 0.1008   | 0.0170            | 0.0388                     | 0.1217             | 0.1165               |
| 0.6871        | 57.0  | 855  | 0.7247          | 0.1024   | 0.0169            | 0.0384                     | 0.1217             | 0.1205               |
| 0.6736        | 58.0  | 870  | 0.7247          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |
| 0.6847        | 59.0  | 885  | 0.7246          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |
| 0.6681        | 60.0  | 900  | 0.7244          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |
| 0.6882        | 61.0  | 915  | 0.7244          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |
| 0.6689        | 62.0  | 930  | 0.7241          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |
| 0.6763        | 63.0  | 945  | 0.7241          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |
| 0.6621        | 64.0  | 960  | 0.7241          | 0.1012   | 0.0160            | 0.0377                     | 0.1190             | 0.1205               |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
