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-0.0001-0.1-lora-layer_4_5_6_7
  results: []
---

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# codet5p-770m-py-sanitized-codebleu-1-True-0.0001-0.1-lora-layer_4_5_6_7

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: 0.7050
- Codebleu: 0.1115
- Ngram Match Score: 0.0243
- Weighted Ngram Match Score: 0.0470
- Syntax Match Score: 0.1243
- Dataflow Match Score: 0.1365

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|
| 0.9786        | 1.0   | 15   | 0.9201          | 0.0072   | 0.0000            | 0.0000                     | 0.0079             | 0.0100               |
| 0.9644        | 2.0   | 30   | 0.9027          | 0.0199   | 0.0000            | 0.0043                     | 0.0185             | 0.0301               |
| 0.9318        | 3.0   | 45   | 0.8679          | 0.0788   | 0.0063            | 0.0310                     | 0.0952             | 0.0924               |
| 0.8745        | 4.0   | 60   | 0.8411          | 0.1008   | 0.0213            | 0.0507                     | 0.1296             | 0.1044               |
| 0.8532        | 5.0   | 75   | 0.8237          | 0.0966   | 0.0211            | 0.0509                     | 0.1190             | 0.1044               |
| 0.829         | 6.0   | 90   | 0.8033          | 0.0961   | 0.0193            | 0.0508                     | 0.1243             | 0.0984               |
| 0.8134        | 7.0   | 105  | 0.7764          | 0.1064   | 0.0161            | 0.0480                     | 0.1376             | 0.1124               |
| 0.7813        | 8.0   | 120  | 0.7549          | 0.0967   | 0.0111            | 0.0329                     | 0.1243             | 0.1064               |
| 0.7574        | 9.0   | 135  | 0.7430          | 0.1048   | 0.0165            | 0.0424                     | 0.1389             | 0.1084               |
| 0.7417        | 10.0  | 150  | 0.7349          | 0.1074   | 0.0185            | 0.0471                     | 0.1296             | 0.1225               |
| 0.7314        | 11.0  | 165  | 0.7287          | 0.1032   | 0.0195            | 0.0467                     | 0.1270             | 0.1145               |
| 0.7247        | 12.0  | 180  | 0.7211          | 0.1035   | 0.0197            | 0.0467                     | 0.1296             | 0.1124               |
| 0.7033        | 13.0  | 195  | 0.7179          | 0.1038   | 0.0166            | 0.0398                     | 0.1270             | 0.1185               |
| 0.682         | 14.0  | 210  | 0.7151          | 0.1078   | 0.0218            | 0.0474                     | 0.1296             | 0.1225               |
| 0.6899        | 15.0  | 225  | 0.7112          | 0.1053   | 0.0165            | 0.0413                     | 0.1283             | 0.1205               |
| 0.6936        | 16.0  | 240  | 0.7072          | 0.1055   | 0.0178            | 0.0418                     | 0.1283             | 0.1205               |
| 0.6714        | 17.0  | 255  | 0.7041          | 0.1072   | 0.0185            | 0.0421                     | 0.1323             | 0.1205               |
| 0.6555        | 18.0  | 270  | 0.7030          | 0.1091   | 0.0211            | 0.0455                     | 0.1336             | 0.1225               |
| 0.6572        | 19.0  | 285  | 0.7005          | 0.1064   | 0.0237            | 0.0478                     | 0.1257             | 0.1225               |
| 0.6385        | 20.0  | 300  | 0.7027          | 0.0958   | 0.0167            | 0.0391                     | 0.1230             | 0.1024               |
| 0.629         | 21.0  | 315  | 0.6986          | 0.0989   | 0.0189            | 0.0414                     | 0.1257             | 0.1064               |
| 0.6183        | 22.0  | 330  | 0.7003          | 0.1040   | 0.0236            | 0.0476                     | 0.1257             | 0.1165               |
| 0.6151        | 23.0  | 345  | 0.7014          | 0.0993   | 0.0191            | 0.0397                     | 0.1230             | 0.1104               |
| 0.6089        | 24.0  | 360  | 0.6978          | 0.1004   | 0.0211            | 0.0437                     | 0.1243             | 0.1104               |
| 0.6182        | 25.0  | 375  | 0.6983          | 0.1053   | 0.0245            | 0.0496                     | 0.1243             | 0.1205               |
| 0.6008        | 26.0  | 390  | 0.6960          | 0.1025   | 0.0208            | 0.0435                     | 0.1217             | 0.1185               |
| 0.5846        | 27.0  | 405  | 0.6981          | 0.0998   | 0.0205            | 0.0432                     | 0.1230             | 0.1104               |
| 0.5919        | 28.0  | 420  | 0.6973          | 0.1000   | 0.0195            | 0.0417                     | 0.1243             | 0.1104               |
| 0.5759        | 29.0  | 435  | 0.6981          | 0.0960   | 0.0208            | 0.0449                     | 0.1190             | 0.1044               |
| 0.5697        | 30.0  | 450  | 0.6991          | 0.0946   | 0.0226            | 0.0453                     | 0.1111             | 0.1084               |
| 0.5687        | 31.0  | 465  | 0.6986          | 0.0986   | 0.0272            | 0.0516                     | 0.1124             | 0.1145               |
| 0.5733        | 32.0  | 480  | 0.7031          | 0.1053   | 0.0273            | 0.0516                     | 0.1190             | 0.1245               |
| 0.5677        | 33.0  | 495  | 0.6964          | 0.1129   | 0.0287            | 0.0544                     | 0.1310             | 0.1305               |
| 0.5764        | 34.0  | 510  | 0.6952          | 0.0988   | 0.0201            | 0.0423                     | 0.1190             | 0.1124               |
| 0.5537        | 35.0  | 525  | 0.7011          | 0.1175   | 0.0301            | 0.0560                     | 0.1376             | 0.1345               |
| 0.578         | 36.0  | 540  | 0.6997          | 0.1136   | 0.0240            | 0.0472                     | 0.1296             | 0.1365               |
| 0.5577        | 37.0  | 555  | 0.7002          | 0.1099   | 0.0254            | 0.0486                     | 0.1296             | 0.1265               |
| 0.5546        | 38.0  | 570  | 0.6941          | 0.1139   | 0.0274            | 0.0517                     | 0.1243             | 0.1406               |
| 0.5467        | 39.0  | 585  | 0.7012          | 0.1068   | 0.0229            | 0.0446                     | 0.1217             | 0.1285               |
| 0.5511        | 40.0  | 600  | 0.7041          | 0.1086   | 0.0219            | 0.0418                     | 0.1270             | 0.1285               |
| 0.5379        | 41.0  | 615  | 0.6995          | 0.1095   | 0.0230            | 0.0446                     | 0.1283             | 0.1285               |
| 0.5434        | 42.0  | 630  | 0.7015          | 0.1170   | 0.0228            | 0.0451                     | 0.1349             | 0.1406               |
| 0.5246        | 43.0  | 645  | 0.6995          | 0.1165   | 0.0279            | 0.0511                     | 0.1310             | 0.1406               |
| 0.5375        | 44.0  | 660  | 0.7019          | 0.1091   | 0.0212            | 0.0446                     | 0.1257             | 0.1305               |
| 0.5286        | 45.0  | 675  | 0.7084          | 0.1099   | 0.0261            | 0.0478                     | 0.1217             | 0.1345               |
| 0.5322        | 46.0  | 690  | 0.7032          | 0.1122   | 0.0260            | 0.0503                     | 0.1310             | 0.1305               |
| 0.538         | 47.0  | 705  | 0.7015          | 0.1178   | 0.0233            | 0.0449                     | 0.1349             | 0.1426               |
| 0.5244        | 48.0  | 720  | 0.7012          | 0.1161   | 0.0263            | 0.0458                     | 0.1217             | 0.1506               |
| 0.5311        | 49.0  | 735  | 0.7000          | 0.1182   | 0.0273            | 0.0503                     | 0.1336             | 0.1426               |
| 0.5088        | 50.0  | 750  | 0.7021          | 0.1221   | 0.0296            | 0.0519                     | 0.1362             | 0.1486               |
| 0.5329        | 51.0  | 765  | 0.7003          | 0.1113   | 0.0231            | 0.0461                     | 0.1243             | 0.1365               |
| 0.5285        | 52.0  | 780  | 0.7035          | 0.1168   | 0.0248            | 0.0460                     | 0.1257             | 0.1486               |
| 0.5174        | 53.0  | 795  | 0.7070          | 0.1127   | 0.0243            | 0.0456                     | 0.1217             | 0.1426               |
| 0.5151        | 54.0  | 810  | 0.7029          | 0.1118   | 0.0235            | 0.0457                     | 0.1217             | 0.1406               |
| 0.5311        | 55.0  | 825  | 0.7044          | 0.1131   | 0.0244            | 0.0471                     | 0.1243             | 0.1406               |
| 0.5241        | 56.0  | 840  | 0.7045          | 0.1051   | 0.0230            | 0.0453                     | 0.1151             | 0.1305               |
| 0.5301        | 57.0  | 855  | 0.7026          | 0.1051   | 0.0230            | 0.0453                     | 0.1151             | 0.1305               |
| 0.5139        | 58.0  | 870  | 0.7027          | 0.1105   | 0.0239            | 0.0452                     | 0.1164             | 0.1426               |
| 0.5293        | 59.0  | 885  | 0.7037          | 0.1126   | 0.0236            | 0.0453                     | 0.1217             | 0.1426               |
| 0.5179        | 60.0  | 900  | 0.7044          | 0.1126   | 0.0236            | 0.0453                     | 0.1217             | 0.1426               |
| 0.5297        | 61.0  | 915  | 0.7059          | 0.1110   | 0.0239            | 0.0454                     | 0.1217             | 0.1386               |
| 0.5207        | 62.0  | 930  | 0.7054          | 0.1102   | 0.0235            | 0.0455                     | 0.1217             | 0.1365               |
| 0.5186        | 63.0  | 945  | 0.7050          | 0.1131   | 0.0240            | 0.0469                     | 0.1243             | 0.1406               |
| 0.5079        | 64.0  | 960  | 0.7050          | 0.1115   | 0.0243            | 0.0470                     | 0.1243             | 0.1365               |


### Framework versions

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