metadata
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/codebert-base-mlm
model-index:
- name: CodeBERTa-commit-message-autocomplete
results: []
CodeBERTa-commit-message-autocomplete
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: 1.8906
- Accuracy: 0.6346
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 4.5523 | 0.3432 |
| No log | 2.0 | 80 | 3.8711 | 0.3796 |
| No log | 3.0 | 120 | 3.2419 | 0.4503 |
| No log | 4.0 | 160 | 2.8709 | 0.4962 |
| No log | 5.0 | 200 | 2.6999 | 0.5085 |
| No log | 6.0 | 240 | 2.6622 | 0.5216 |
| No log | 7.0 | 280 | 2.5048 | 0.5410 |
| No log | 8.0 | 320 | 2.4249 | 0.5581 |
| No log | 9.0 | 360 | 2.3727 | 0.5623 |
| No log | 10.0 | 400 | 2.3625 | 0.5665 |
| No log | 11.0 | 440 | 2.3320 | 0.5706 |
| No log | 12.0 | 480 | 2.1704 | 0.5950 |
| 3.081 | 13.0 | 520 | 2.2109 | 0.5893 |
| 3.081 | 14.0 | 560 | 2.2330 | 0.5884 |
| 3.081 | 15.0 | 600 | 2.1454 | 0.5954 |
| 3.081 | 16.0 | 640 | 2.1740 | 0.5951 |
| 3.081 | 17.0 | 680 | 2.1219 | 0.5920 |
| 3.081 | 18.0 | 720 | 2.1136 | 0.6052 |
| 3.081 | 19.0 | 760 | 2.0586 | 0.6127 |
| 3.081 | 20.0 | 800 | 2.0185 | 0.6113 |
| 3.081 | 21.0 | 840 | 2.0493 | 0.6129 |
| 3.081 | 22.0 | 880 | 1.9766 | 0.6217 |
| 3.081 | 23.0 | 920 | 1.9968 | 0.6189 |
| 3.081 | 24.0 | 960 | 1.9567 | 0.6276 |
| 2.122 | 25.0 | 1000 | 1.9611 | 0.6269 |
| 2.122 | 26.0 | 1040 | 1.9437 | 0.6254 |
| 2.122 | 27.0 | 1080 | 1.9865 | 0.6266 |
| 2.122 | 28.0 | 1120 | 1.9112 | 0.6295 |
| 2.122 | 29.0 | 1160 | 1.8903 | 0.6292 |
| 2.122 | 30.0 | 1200 | 1.8992 | 0.6376 |
| 2.122 | 31.0 | 1240 | 1.9122 | 0.6327 |
| 2.122 | 32.0 | 1280 | 1.8906 | 0.6346 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2