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: 0.3131
- Accuracy: 0.9207
- Best Accuracy: 0.9207
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: 2.34314e-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: 813
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Best Accuracy |
|---|---|---|---|---|---|
| 0.4448 | 0.17 | 163 | 0.2735 | 0.9066 | 0.9066 |
| 0.2779 | 0.33 | 326 | 0.2817 | 0.9185 | 0.9185 |
| 0.1733 | 0.5 | 489 | 0.3446 | 0.9027 | 0.9185 |
| 0.1861 | 0.66 | 652 | 0.3131 | 0.9207 | 0.9207 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3