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---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: CommitPredictorT5
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. -->
# CommitPredictorT5
This model is a fine-tuned version of [Salesforce/codet5-base-multi-sum](https://huggingface.co/Salesforce/codet5-base-multi-sum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7376
- Rouge1: 0.3735
- Rouge2: 0.1504
- Rougel: 0.3701
- Rougelsum: 0.3697
- Gen Len: 19.1365
- Bleu: 0.1453
## 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: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|
| 3.2138 | 1.0 | 687 | 2.6919 | 0.3246 | 0.0964 | 0.3216 | 0.3218 | 9.125 | 0.0937 |
| 2.7517 | 2.0 | 1374 | 2.5546 | 0.3394 | 0.1042 | 0.3364 | 0.3362 | 8.9803 | 0.1066 |
| 2.4305 | 3.0 | 2061 | 2.4836 | 0.3523 | 0.1136 | 0.3496 | 0.3496 | 9.2049 | 0.1123 |
| 2.2956 | 4.0 | 2748 | 2.4483 | 0.3658 | 0.126 | 0.3633 | 0.3633 | 9.525 | 0.1146 |
| 2.1888 | 5.0 | 3435 | 2.4312 | 0.3665 | 0.1332 | 0.3636 | 0.3634 | 10.0631 | 0.1253 |
| 2.0056 | 6.0 | 4122 | 2.4251 | 0.3674 | 0.1352 | 0.3646 | 0.3644 | 9.8365 | 0.1240 |
| 1.9128 | 7.0 | 4809 | 2.4289 | 0.3725 | 0.1431 | 0.3694 | 0.3694 | 9.8713 | 0.1295 |
| 1.8487 | 8.0 | 5496 | 2.4625 | 0.3683 | 0.1377 | 0.3657 | 0.3659 | 10.0947 | 0.1291 |
| 1.6726 | 9.0 | 6183 | 2.4643 | 0.3725 | 0.1449 | 0.3702 | 0.3697 | 13.1967 | 0.1325 |
| 1.6292 | 10.0 | 6870 | 2.4716 | 0.3688 | 0.1438 | 0.3664 | 0.3661 | 13.7656 | 0.1307 |
| 1.5025 | 11.0 | 7557 | 2.4974 | 0.3762 | 0.1494 | 0.3732 | 0.3732 | 14.0988 | 0.1391 |
| 1.4224 | 12.0 | 8244 | 2.5273 | 0.3723 | 0.1489 | 0.3692 | 0.3688 | 12.084 | 0.1388 |
| 1.3912 | 13.0 | 8931 | 2.5460 | 0.375 | 0.1499 | 0.3722 | 0.3723 | 13.9529 | 0.1399 |
| 1.2766 | 14.0 | 9618 | 2.5771 | 0.3698 | 0.1453 | 0.3668 | 0.3667 | 12.5102 | 0.1386 |
| 1.2188 | 15.0 | 10305 | 2.6005 | 0.3789 | 0.1493 | 0.3763 | 0.376 | 16.0545 | 0.1423 |
| 1.1779 | 16.0 | 10992 | 2.6296 | 0.3757 | 0.1497 | 0.3729 | 0.3723 | 14.7201 | 0.1423 |
| 1.0739 | 17.0 | 11679 | 2.6512 | 0.3749 | 0.1522 | 0.3717 | 0.3715 | 16.0008 | 0.1468 |
| 1.0408 | 18.0 | 12366 | 2.6792 | 0.3758 | 0.1494 | 0.3735 | 0.3733 | 18.4971 | 0.1465 |
| 0.9567 | 19.0 | 13053 | 2.7153 | 0.3695 | 0.144 | 0.3669 | 0.3667 | 16.2357 | 0.1435 |
| 0.9072 | 20.0 | 13740 | 2.7376 | 0.3735 | 0.1504 | 0.3701 | 0.3697 | 19.1365 | 0.1453 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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