--- 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-1e-06-0.1-prefix-tuning results: [] --- # codet5p-770m-py-sanitized-codebleu-1-True-1e-06-0.1-prefix-tuning 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: 9.3690 - Codebleu: 0.0440 - Ngram Match Score: 0.0003 - Weighted Ngram Match Score: 0.0003 - Syntax Match Score: 0.0013 - Dataflow Match Score: 0.1084 ## 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: 1e-06 - train_batch_size: 16 - eval_batch_size: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:| | 9.311 | 1.0 | 8 | 9.4023 | 0.0488 | 0.0003 | 0.0003 | 0.0013 | 0.1205 | | 9.1929 | 2.0 | 16 | 9.4021 | 0.0488 | 0.0003 | 0.0003 | 0.0013 | 0.1205 | | 9.2718 | 3.0 | 24 | 9.4019 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.1752 | 4.0 | 32 | 9.4015 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.1592 | 5.0 | 40 | 9.4010 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.1841 | 6.0 | 48 | 9.4005 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.2778 | 7.0 | 56 | 9.3998 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.2436 | 8.0 | 64 | 9.3991 | 0.0480 | 0.0004 | 0.0003 | 0.0013 | 0.1185 | | 9.1964 | 9.0 | 72 | 9.3983 | 0.0480 | 0.0004 | 0.0003 | 0.0013 | 0.1185 | | 9.1678 | 10.0 | 80 | 9.3974 | 0.0480 | 0.0004 | 0.0003 | 0.0013 | 0.1185 | | 9.2327 | 11.0 | 88 | 9.3963 | 0.0480 | 0.0004 | 0.0003 | 0.0013 | 0.1185 | | 9.2025 | 12.0 | 96 | 9.3950 | 0.0480 | 0.0004 | 0.0003 | 0.0013 | 0.1185 | | 9.202 | 13.0 | 104 | 9.3937 | 0.0480 | 0.0004 | 0.0003 | 0.0013 | 0.1185 | | 9.2192 | 14.0 | 112 | 9.3924 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.1797 | 15.0 | 120 | 9.3911 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.1952 | 16.0 | 128 | 9.3901 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.1932 | 17.0 | 136 | 9.3891 | 0.0480 | 0.0003 | 0.0003 | 0.0013 | 0.1185 | | 9.2271 | 18.0 | 144 | 9.3880 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.2241 | 19.0 | 152 | 9.3869 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.2655 | 20.0 | 160 | 9.3857 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.1865 | 21.0 | 168 | 9.3846 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.1816 | 22.0 | 176 | 9.3834 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.1961 | 23.0 | 184 | 9.3824 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.1911 | 24.0 | 192 | 9.3814 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.1785 | 25.0 | 200 | 9.3805 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.1715 | 26.0 | 208 | 9.3797 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.2293 | 27.0 | 216 | 9.3788 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.2066 | 28.0 | 224 | 9.3780 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.2515 | 29.0 | 232 | 9.3772 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.198 | 30.0 | 240 | 9.3764 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.2351 | 31.0 | 248 | 9.3758 | 0.0464 | 0.0003 | 0.0003 | 0.0013 | 0.1145 | | 9.228 | 32.0 | 256 | 9.3751 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2185 | 33.0 | 264 | 9.3744 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1991 | 34.0 | 272 | 9.3738 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2657 | 35.0 | 280 | 9.3732 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1871 | 36.0 | 288 | 9.3726 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1871 | 37.0 | 296 | 9.3721 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2122 | 38.0 | 304 | 9.3716 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2057 | 39.0 | 312 | 9.3712 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2578 | 40.0 | 320 | 9.3708 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1719 | 41.0 | 328 | 9.3704 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1942 | 42.0 | 336 | 9.3701 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2253 | 43.0 | 344 | 9.3698 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1445 | 44.0 | 352 | 9.3696 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2078 | 45.0 | 360 | 9.3694 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.23 | 46.0 | 368 | 9.3692 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1418 | 47.0 | 376 | 9.3691 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.2528 | 48.0 | 384 | 9.3690 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1605 | 49.0 | 392 | 9.3690 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | | 9.1709 | 50.0 | 400 | 9.3690 | 0.0440 | 0.0003 | 0.0003 | 0.0013 | 0.1084 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1 - Datasets 2.14.4 - Tokenizers 0.13.3