metadata
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: oo-method-test-model-bylibrary
results: []
oo-method-test-model-bylibrary
This model is a fine-tuned version of huggingface/CodeBERTa-small-v1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1651
- Accuracy: 0.9439
- Best Accuracy: 0.9439
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: 1.238e-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: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 915
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Best Accuracy |
|---|---|---|---|---|---|
| 0.4914 | 0.19 | 183 | 0.2747 | 0.8956 | 0.8956 |
| 0.2639 | 0.37 | 366 | 0.3623 | 0.8925 | 0.8956 |
| 0.2105 | 0.56 | 549 | 0.2257 | 0.9224 | 0.9224 |
| 0.1669 | 0.74 | 732 | 0.1651 | 0.9439 | 0.9439 |
| 0.1037 | 0.93 | 915 | 0.1676 | 0.9408 | 0.9439 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3