metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CommitPredictor
results: []
CommitPredictor
This model is a fine-tuned version of microsoft/codebert-base-mlm on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5343
- Accuracy: 0.8907
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: 1.4577896002135506e-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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7923 | 1.0 | 2440 | 0.6680 | 0.8628 |
| 0.6992 | 2.0 | 4880 | 0.6148 | 0.8749 |
| 0.6624 | 3.0 | 7320 | 0.5993 | 0.8781 |
| 0.63 | 4.0 | 9760 | 0.5683 | 0.8831 |
| 0.5944 | 5.0 | 12200 | 0.5525 | 0.8868 |
| 0.5886 | 6.0 | 14640 | 0.5470 | 0.8879 |
| 0.5888 | 7.0 | 17080 | 0.5478 | 0.8879 |
| 0.5668 | 8.0 | 19520 | 0.5385 | 0.8889 |
| 0.5714 | 9.0 | 21960 | 0.5390 | 0.8892 |
| 0.5702 | 10.0 | 24400 | 0.5343 | 0.8907 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2