--- license: bsd-3-clause tags: - generated_from_trainer datasets: - mbpp model-index: - name: codet5p-770m-py-codebleu-32-True-1e-06-0.1 results: [] --- # codet5p-770m-py-codebleu-32-True-1e-06-0.1 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: 0.8087 - Codebleu: 0.0867 - Ngram Match Score: 0.0137 - Weighted Ngram Match Score: 0.0422 - Syntax Match Score: 0.1204 - Dataflow Match Score: 0.0824 ## 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: 6 - eval_batch_size: 6 - seed: 42 - gradient_accumulation_steps: 32 - total_train_batch_size: 192 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 50 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Codebleu | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:| | 1.9228 | 0.51 | 1 | 0.9113 | 0.0047 | 0.0000 | 0.0000 | 0.0048 | 0.0070 | | 0.9857 | 1.52 | 3 | 0.9112 | 0.0047 | 0.0000 | 0.0000 | 0.0048 | 0.0070 | | 0.9734 | 2.54 | 5 | 0.9112 | 0.0069 | 0.0000 | 0.0001 | 0.0067 | 0.0105 | | 0.9624 | 3.56 | 7 | 0.9111 | 0.0074 | 0.0000 | 0.0002 | 0.0072 | 0.0112 | | 0.9586 | 4.57 | 9 | 0.9107 | 0.0087 | 0.0000 | 0.0003 | 0.0092 | 0.0126 | | 0.9708 | 5.59 | 11 | 0.9097 | 0.0140 | 0.0000 | 0.0019 | 0.0178 | 0.0168 | | 0.9667 | 6.6 | 13 | 0.9092 | 0.0171 | 0.0000 | 0.0034 | 0.0202 | 0.0216 | | 0.9791 | 7.62 | 15 | 0.9058 | 0.0211 | 0.0000 | 0.0057 | 0.0255 | 0.0258 | | 0.9702 | 8.63 | 17 | 0.9048 | 0.0317 | 0.0001 | 0.0144 | 0.0366 | 0.0391 | | 0.9563 | 9.65 | 19 | 0.9034 | 0.0398 | 0.0007 | 0.0192 | 0.0477 | 0.0468 | | 0.9654 | 10.67 | 21 | 0.8927 | 0.0482 | 0.0014 | 0.0215 | 0.0583 | 0.0566 | | 0.9458 | 11.68 | 23 | 0.8898 | 0.0602 | 0.0043 | 0.0275 | 0.0742 | 0.0684 | | 0.9523 | 12.7 | 25 | 0.8866 | 0.0647 | 0.0053 | 0.0286 | 0.0829 | 0.0705 | | 0.942 | 13.71 | 27 | 0.8847 | 0.0786 | 0.0091 | 0.0338 | 0.1069 | 0.0789 | | 0.94 | 14.73 | 29 | 0.8648 | 0.0798 | 0.0099 | 0.0357 | 0.1079 | 0.0803 | | 0.9025 | 15.75 | 31 | 0.8604 | 0.0809 | 0.0105 | 0.0363 | 0.1122 | 0.0782 | | 0.9058 | 16.76 | 33 | 0.8577 | 0.0815 | 0.0107 | 0.0362 | 0.1132 | 0.0789 | | 0.893 | 17.78 | 35 | 0.8543 | 0.0816 | 0.0110 | 0.0363 | 0.1132 | 0.0789 | | 0.8959 | 18.79 | 37 | 0.8524 | 0.0805 | 0.0109 | 0.0362 | 0.1113 | 0.0782 | | 0.877 | 19.81 | 39 | 0.8422 | 0.0808 | 0.0118 | 0.0385 | 0.1113 | 0.0782 | | 0.861 | 20.83 | 41 | 0.8374 | 0.0811 | 0.0118 | 0.0385 | 0.1113 | 0.0789 | | 0.8365 | 21.84 | 43 | 0.8376 | 0.0827 | 0.0119 | 0.0386 | 0.1132 | 0.0810 | | 0.8293 | 22.86 | 45 | 0.8331 | 0.0853 | 0.0126 | 0.0390 | 0.1180 | 0.0824 | | 0.8288 | 23.87 | 47 | 0.8246 | 0.0852 | 0.0134 | 0.0421 | 0.1180 | 0.0810 | | 0.8175 | 24.89 | 49 | 0.8141 | 0.0852 | 0.0134 | 0.0421 | 0.1180 | 0.0810 | | 0.6345 | 25.4 | 50 | 0.8087 | 0.0867 | 0.0137 | 0.0422 | 0.1204 | 0.0824 | ### Framework versions - Transformers 4.30.0.dev0 - Pytorch 2.0.1 - Datasets 2.13.1 - Tokenizers 0.13.3