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---
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: oo-method-test-model-bylibrary
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. -->
# oo-method-test-model-bylibrary
This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on the ejschwartz/oo-method-test-split dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3303
- Accuracy: 0.9161
- Best Accuracy: 0.9161
## 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: 2.386135927313411e-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: 887
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Best Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|
| 0.3788 | 0.02 | 178 | 0.6188 | 0.8470 | 0.8470 |
| 0.1456 | 0.04 | 356 | 0.6572 | 0.8519 | 0.8519 |
| 0.17 | 0.05 | 534 | 0.4926 | 0.8798 | 0.8798 |
| 0.1162 | 0.07 | 712 | 0.3303 | 0.9161 | 0.9161 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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