File size: 3,439 Bytes
ec36b04 8d828b6 91daf39 ec36b04 8d828b6 113a6c0 ec36b04 6587462 113a6c0 ec36b04 113a6c0 8d828b6 113a6c0 8d828b6 ec36b04 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: CommitPredictor
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. -->
# CommitPredictor
This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4812
- Accuracy: 0.8993
- F1: 0.8993
- Bleu4: 0.9483
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
| 1.1319 | 1.0 | 687 | 0.6982 | 0.8562 | 0.8562 | 0.8551 |
| 0.7784 | 2.0 | 1374 | 0.6501 | 0.8665 | 0.8665 | 0.8977 |
| 0.6779 | 3.0 | 2061 | 0.6229 | 0.8733 | 0.8733 | 0.8535 |
| 0.6579 | 4.0 | 2748 | 0.5978 | 0.8769 | 0.8769 | 0.9176 |
| 0.6319 | 5.0 | 3435 | 0.5833 | 0.8808 | 0.8808 | 0.8073 |
| 0.5988 | 6.0 | 4122 | 0.5627 | 0.8834 | 0.8834 | 0.9241 |
| 0.5939 | 7.0 | 4809 | 0.5533 | 0.8864 | 0.8864 | 0.9212 |
| 0.575 | 8.0 | 5496 | 0.5512 | 0.8860 | 0.8860 | 0.7943 |
| 0.5574 | 9.0 | 6183 | 0.5412 | 0.8879 | 0.8879 | 0.9396 |
| 0.553 | 10.0 | 6870 | 0.5276 | 0.8899 | 0.8899 | 0.8301 |
| 0.5371 | 11.0 | 7557 | 0.5341 | 0.8893 | 0.8893 | 0.9350 |
| 0.5302 | 12.0 | 8244 | 0.5236 | 0.8909 | 0.8909 | 0.8813 |
| 0.5245 | 13.0 | 8931 | 0.5153 | 0.8933 | 0.8933 | 0.8817 |
| 0.5165 | 14.0 | 9618 | 0.5138 | 0.8926 | 0.8926 | 0.9174 |
| 0.5122 | 15.0 | 10305 | 0.5144 | 0.8930 | 0.8930 | 0.8318 |
| 0.5007 | 16.0 | 10992 | 0.5007 | 0.8957 | 0.8957 | 0.9350 |
| 0.4954 | 17.0 | 11679 | 0.5041 | 0.8960 | 0.8960 | 0.9355 |
| 0.4894 | 18.0 | 12366 | 0.5000 | 0.8967 | 0.8967 | 0.7818 |
| 0.4851 | 19.0 | 13053 | 0.4915 | 0.8982 | 0.8982 | 0.9190 |
| 0.483 | 20.0 | 13740 | 0.4970 | 0.8962 | 0.8962 | 0.9359 |
| 0.4792 | 21.0 | 14427 | 0.4849 | 0.8971 | 0.8971 | 0.8458 |
| 0.4716 | 22.0 | 15114 | 0.4809 | 0.8990 | 0.8990 | 0.9367 |
| 0.4691 | 23.0 | 15801 | 0.4732 | 0.9006 | 0.9006 | 0.9478 |
| 0.4675 | 24.0 | 16488 | 0.4805 | 0.8989 | 0.8989 | 0.9412 |
| 0.4618 | 25.0 | 17175 | 0.4837 | 0.8997 | 0.8997 | 0.8373 |
| 0.4633 | 26.0 | 17862 | 0.4812 | 0.8993 | 0.8993 | 0.9483 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
|