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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

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

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: 0.6873
- Codebleu: 0.1244
- Ngram Match Score: 0.0258
- Weighted Ngram Match Score: 0.0520
- Syntax Match Score: 0.1310
- Dataflow Match Score: 0.1606

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Codebleu | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|
| 0.9871        | 1.0   | 15   | 0.9197          | 0.0072   | 0.0000            | 0.0000                     | 0.0079             | 0.0100               |
| 0.9599        | 2.0   | 30   | 0.9009          | 0.0200   | 0.0000            | 0.0053                     | 0.0185             | 0.0301               |
| 0.9303        | 3.0   | 45   | 0.8654          | 0.0833   | 0.0193            | 0.0474                     | 0.1032             | 0.0884               |
| 0.8725        | 4.0   | 60   | 0.8467          | 0.1005   | 0.0209            | 0.0503                     | 0.1270             | 0.1064               |
| 0.8613        | 5.0   | 75   | 0.8336          | 0.1007   | 0.0238            | 0.0521                     | 0.1243             | 0.1084               |
| 0.836         | 6.0   | 90   | 0.8153          | 0.1005   | 0.0232            | 0.0512                     | 0.1323             | 0.1004               |
| 0.8286        | 7.0   | 105  | 0.7953          | 0.0984   | 0.0236            | 0.0514                     | 0.1270             | 0.1004               |
| 0.8074        | 8.0   | 120  | 0.7667          | 0.1036   | 0.0249            | 0.0563                     | 0.1283             | 0.1104               |
| 0.7782        | 9.0   | 135  | 0.7399          | 0.0960   | 0.0136            | 0.0416                     | 0.1217             | 0.1044               |
| 0.7638        | 10.0  | 150  | 0.7282          | 0.1033   | 0.0174            | 0.0503                     | 0.1270             | 0.1145               |
| 0.7551        | 11.0  | 165  | 0.7236          | 0.1038   | 0.0192            | 0.0502                     | 0.1257             | 0.1165               |
| 0.7538        | 12.0  | 180  | 0.7178          | 0.1084   | 0.0185            | 0.0518                     | 0.1349             | 0.1185               |
| 0.7446        | 13.0  | 195  | 0.7139          | 0.1081   | 0.0198            | 0.0528                     | 0.1376             | 0.1145               |
| 0.7465        | 14.0  | 210  | 0.7103          | 0.1065   | 0.0172            | 0.0444                     | 0.1323             | 0.1185               |
| 0.7728        | 15.0  | 225  | 0.7065          | 0.1117   | 0.0233            | 0.0541                     | 0.1415             | 0.1185               |
| 0.7455        | 16.0  | 240  | 0.7033          | 0.1107   | 0.0247            | 0.0525                     | 0.1429             | 0.1145               |
| 0.7309        | 17.0  | 255  | 0.7017          | 0.1199   | 0.0270            | 0.0544                     | 0.1508             | 0.1285               |
| 0.7172        | 18.0  | 270  | 0.6992          | 0.1161   | 0.0238            | 0.0514                     | 0.1429             | 0.1285               |
| 0.7241        | 19.0  | 285  | 0.6979          | 0.1183   | 0.0259            | 0.0530                     | 0.1495             | 0.1265               |
| 0.7132        | 20.0  | 300  | 0.6966          | 0.1126   | 0.0245            | 0.0512                     | 0.1442             | 0.1185               |
| 0.6995        | 21.0  | 315  | 0.6936          | 0.1193   | 0.0262            | 0.0550                     | 0.1534             | 0.1245               |
| 0.6916        | 22.0  | 330  | 0.6926          | 0.1127   | 0.0230            | 0.0482                     | 0.1415             | 0.1225               |
| 0.6873        | 23.0  | 345  | 0.6913          | 0.1152   | 0.0255            | 0.0513                     | 0.1442             | 0.1245               |
| 0.6884        | 24.0  | 360  | 0.6908          | 0.1157   | 0.0238            | 0.0471                     | 0.1389             | 0.1325               |
| 0.7025        | 25.0  | 375  | 0.6895          | 0.1133   | 0.0241            | 0.0471                     | 0.1389             | 0.1265               |
| 0.6857        | 26.0  | 390  | 0.6885          | 0.1093   | 0.0217            | 0.0468                     | 0.1296             | 0.1265               |
| 0.6669        | 27.0  | 405  | 0.6894          | 0.1107   | 0.0201            | 0.0463                     | 0.1296             | 0.1305               |
| 0.6842        | 28.0  | 420  | 0.6866          | 0.1053   | 0.0220            | 0.0489                     | 0.1230             | 0.1225               |
| 0.6606        | 29.0  | 435  | 0.6866          | 0.1112   | 0.0227            | 0.0486                     | 0.1217             | 0.1386               |
| 0.6648        | 30.0  | 450  | 0.6868          | 0.1070   | 0.0209            | 0.0478                     | 0.1177             | 0.1325               |
| 0.6615        | 31.0  | 465  | 0.6856          | 0.1091   | 0.0223            | 0.0493                     | 0.1283             | 0.1265               |
| 0.6616        | 32.0  | 480  | 0.6871          | 0.1104   | 0.0226            | 0.0484                     | 0.1217             | 0.1365               |
| 0.663         | 33.0  | 495  | 0.6876          | 0.1076   | 0.0240            | 0.0511                     | 0.1257             | 0.1245               |
| 0.6632        | 34.0  | 510  | 0.6876          | 0.1042   | 0.0237            | 0.0497                     | 0.1257             | 0.1165               |
| 0.6548        | 35.0  | 525  | 0.6882          | 0.1148   | 0.0246            | 0.0501                     | 0.1217             | 0.1466               |
| 0.6778        | 36.0  | 540  | 0.6848          | 0.1114   | 0.0224            | 0.0502                     | 0.1217             | 0.1386               |
| 0.6517        | 37.0  | 555  | 0.6866          | 0.1180   | 0.0234            | 0.0490                     | 0.1283             | 0.1486               |
| 0.6576        | 38.0  | 570  | 0.6876          | 0.1219   | 0.0248            | 0.0519                     | 0.1349             | 0.1506               |
| 0.6504        | 39.0  | 585  | 0.6862          | 0.1224   | 0.0237            | 0.0501                     | 0.1310             | 0.1566               |
| 0.6558        | 40.0  | 600  | 0.6871          | 0.1242   | 0.0249            | 0.0507                     | 0.1349             | 0.1566               |
| 0.6426        | 41.0  | 615  | 0.6876          | 0.1290   | 0.0288            | 0.0546                     | 0.1389             | 0.1627               |
| 0.6533        | 42.0  | 630  | 0.6868          | 0.1246   | 0.0244            | 0.0501                     | 0.1323             | 0.1606               |
| 0.6396        | 43.0  | 645  | 0.6876          | 0.1226   | 0.0270            | 0.0539                     | 0.1336             | 0.1526               |
| 0.6488        | 44.0  | 660  | 0.6873          | 0.1226   | 0.0270            | 0.0538                     | 0.1336             | 0.1526               |
| 0.6419        | 45.0  | 675  | 0.6876          | 0.1282   | 0.0264            | 0.0525                     | 0.1402             | 0.1606               |
| 0.6443        | 46.0  | 690  | 0.6874          | 0.1221   | 0.0264            | 0.0523                     | 0.1310             | 0.1546               |
| 0.6499        | 47.0  | 705  | 0.6875          | 0.1200   | 0.0264            | 0.0523                     | 0.1257             | 0.1546               |
| 0.6402        | 48.0  | 720  | 0.6874          | 0.1244   | 0.0258            | 0.0520                     | 0.1310             | 0.1606               |
| 0.6552        | 49.0  | 735  | 0.6872          | 0.1244   | 0.0258            | 0.0520                     | 0.1310             | 0.1606               |
| 0.6296        | 50.0  | 750  | 0.6873          | 0.1244   | 0.0258            | 0.0520                     | 0.1310             | 0.1606               |


### Framework versions

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