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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_21
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# codet5p-770m-py-sanitized-codebleu-1-True-5e-05-0.1-lora-layer_21
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: 0.7161
- Codebleu: 0.1126
- Ngram Match Score: 0.0280
- Weighted Ngram Match Score: 0.0604
- Syntax Match Score: 0.1389
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|
| 0.9738 | 1.0 | 15 | 0.9247 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 |
| 0.9612 | 2.0 | 30 | 0.9236 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 |
| 0.9731 | 3.0 | 45 | 0.9209 | 0.0072 | 0.0000 | 0.0000 | 0.0079 | 0.0100 |
| 0.9424 | 4.0 | 60 | 0.9145 | 0.0080 | 0.0000 | 0.0000 | 0.0079 | 0.0120 |
| 0.9588 | 5.0 | 75 | 0.9004 | 0.0104 | 0.0000 | 0.0003 | 0.0079 | 0.0181 |
| 0.9447 | 6.0 | 90 | 0.8748 | 0.0543 | 0.0018 | 0.0269 | 0.0622 | 0.0663 |
| 0.9237 | 7.0 | 105 | 0.8428 | 0.0921 | 0.0207 | 0.0498 | 0.1204 | 0.0924 |
| 0.8665 | 8.0 | 120 | 0.8210 | 0.0996 | 0.0220 | 0.0507 | 0.1283 | 0.1024 |
| 0.8448 | 9.0 | 135 | 0.8068 | 0.0993 | 0.0213 | 0.0493 | 0.1323 | 0.0984 |
| 0.8224 | 10.0 | 150 | 0.7944 | 0.1001 | 0.0205 | 0.0495 | 0.1323 | 0.1004 |
| 0.8045 | 11.0 | 165 | 0.7813 | 0.1042 | 0.0187 | 0.0471 | 0.1336 | 0.1104 |
| 0.8003 | 12.0 | 180 | 0.7709 | 0.1010 | 0.0181 | 0.0474 | 0.1257 | 0.1104 |
| 0.7818 | 13.0 | 195 | 0.7654 | 0.0983 | 0.0181 | 0.0476 | 0.1230 | 0.1064 |
| 0.7641 | 14.0 | 210 | 0.7610 | 0.0984 | 0.0188 | 0.0476 | 0.1230 | 0.1064 |
| 0.7824 | 15.0 | 225 | 0.7570 | 0.0952 | 0.0168 | 0.0438 | 0.1164 | 0.1064 |
| 0.7851 | 16.0 | 240 | 0.7540 | 0.0960 | 0.0194 | 0.0495 | 0.1164 | 0.1064 |
| 0.7675 | 17.0 | 255 | 0.7512 | 0.0944 | 0.0192 | 0.0495 | 0.1124 | 0.1064 |
| 0.7507 | 18.0 | 270 | 0.7487 | 0.0959 | 0.0185 | 0.0494 | 0.1124 | 0.1104 |
| 0.7612 | 19.0 | 285 | 0.7459 | 0.0932 | 0.0178 | 0.0490 | 0.1098 | 0.1064 |
| 0.7476 | 20.0 | 300 | 0.7433 | 0.0933 | 0.0186 | 0.0497 | 0.1138 | 0.1024 |
| 0.7357 | 21.0 | 315 | 0.7410 | 0.1083 | 0.0241 | 0.0607 | 0.1270 | 0.1225 |
| 0.7371 | 22.0 | 330 | 0.7384 | 0.0961 | 0.0152 | 0.0387 | 0.1204 | 0.1064 |
| 0.733 | 23.0 | 345 | 0.7368 | 0.0932 | 0.0152 | 0.0388 | 0.1151 | 0.1044 |
| 0.7354 | 24.0 | 360 | 0.7353 | 0.0924 | 0.0154 | 0.0390 | 0.1111 | 0.1064 |
| 0.7527 | 25.0 | 375 | 0.7336 | 0.0915 | 0.0150 | 0.0384 | 0.1111 | 0.1044 |
| 0.7314 | 26.0 | 390 | 0.7323 | 0.0975 | 0.0196 | 0.0451 | 0.1190 | 0.1084 |
| 0.7167 | 27.0 | 405 | 0.7313 | 0.0975 | 0.0196 | 0.0451 | 0.1190 | 0.1084 |
| 0.7248 | 28.0 | 420 | 0.7303 | 0.1004 | 0.0212 | 0.0491 | 0.1230 | 0.1104 |
| 0.7101 | 29.0 | 435 | 0.7290 | 0.0999 | 0.0230 | 0.0507 | 0.1230 | 0.1084 |
| 0.7138 | 30.0 | 450 | 0.7280 | 0.1064 | 0.0288 | 0.0612 | 0.1270 | 0.1165 |
| 0.7087 | 31.0 | 465 | 0.7270 | 0.1034 | 0.0285 | 0.0610 | 0.1217 | 0.1145 |
| 0.7068 | 32.0 | 480 | 0.7263 | 0.1063 | 0.0285 | 0.0608 | 0.1270 | 0.1165 |
| 0.7101 | 33.0 | 495 | 0.7260 | 0.1063 | 0.0285 | 0.0608 | 0.1270 | 0.1165 |
| 0.7124 | 34.0 | 510 | 0.7241 | 0.1034 | 0.0285 | 0.0610 | 0.1217 | 0.1145 |
| 0.6968 | 35.0 | 525 | 0.7233 | 0.1034 | 0.0285 | 0.0610 | 0.1217 | 0.1145 |
| 0.7215 | 36.0 | 540 | 0.7224 | 0.1005 | 0.0264 | 0.0603 | 0.1190 | 0.1104 |
| 0.703 | 37.0 | 555 | 0.7219 | 0.1052 | 0.0264 | 0.0599 | 0.1270 | 0.1145 |
| 0.7096 | 38.0 | 570 | 0.7216 | 0.1023 | 0.0264 | 0.0601 | 0.1217 | 0.1124 |
| 0.7004 | 39.0 | 585 | 0.7208 | 0.1080 | 0.0296 | 0.0631 | 0.1283 | 0.1185 |
| 0.7109 | 40.0 | 600 | 0.7206 | 0.1048 | 0.0281 | 0.0597 | 0.1257 | 0.1145 |
| 0.6934 | 41.0 | 615 | 0.7201 | 0.1048 | 0.0281 | 0.0597 | 0.1257 | 0.1145 |
| 0.6898 | 42.0 | 630 | 0.7194 | 0.1024 | 0.0273 | 0.0596 | 0.1217 | 0.1124 |
| 0.6905 | 43.0 | 645 | 0.7192 | 0.1073 | 0.0298 | 0.0612 | 0.1310 | 0.1145 |
| 0.6982 | 44.0 | 660 | 0.7188 | 0.1083 | 0.0308 | 0.0647 | 0.1283 | 0.1185 |
| 0.6946 | 45.0 | 675 | 0.7186 | 0.1111 | 0.0304 | 0.0645 | 0.1336 | 0.1205 |
| 0.6861 | 46.0 | 690 | 0.7186 | 0.1133 | 0.0310 | 0.0645 | 0.1389 | 0.1205 |
| 0.6923 | 47.0 | 705 | 0.7180 | 0.1105 | 0.0282 | 0.0603 | 0.1336 | 0.1205 |
| 0.6888 | 48.0 | 720 | 0.7177 | 0.1105 | 0.0282 | 0.0603 | 0.1336 | 0.1205 |
| 0.6922 | 49.0 | 735 | 0.7174 | 0.1105 | 0.0282 | 0.0603 | 0.1336 | 0.1205 |
| 0.684 | 50.0 | 750 | 0.7174 | 0.1105 | 0.0282 | 0.0603 | 0.1336 | 0.1205 |
| 0.7088 | 51.0 | 765 | 0.7172 | 0.1096 | 0.0276 | 0.0603 | 0.1336 | 0.1185 |
| 0.698 | 52.0 | 780 | 0.7167 | 0.1067 | 0.0276 | 0.0605 | 0.1283 | 0.1165 |
| 0.699 | 53.0 | 795 | 0.7165 | 0.1067 | 0.0276 | 0.0605 | 0.1283 | 0.1165 |
| 0.6646 | 54.0 | 810 | 0.7165 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.689 | 55.0 | 825 | 0.7163 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.6882 | 56.0 | 840 | 0.7161 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.6893 | 57.0 | 855 | 0.7161 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.6833 | 58.0 | 870 | 0.7161 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.6994 | 59.0 | 885 | 0.7160 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.679 | 60.0 | 900 | 0.7160 | 0.1118 | 0.0282 | 0.0604 | 0.1389 | 0.1185 |
| 0.6921 | 61.0 | 915 | 0.7161 | 0.1126 | 0.0280 | 0.0604 | 0.1389 | 0.1205 |
| 0.6759 | 62.0 | 930 | 0.7161 | 0.1126 | 0.0280 | 0.0604 | 0.1389 | 0.1205 |
| 0.6861 | 63.0 | 945 | 0.7161 | 0.1126 | 0.0280 | 0.0604 | 0.1389 | 0.1205 |
| 0.6737 | 64.0 | 960 | 0.7161 | 0.1126 | 0.0280 | 0.0604 | 0.1389 | 0.1205 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
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