---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: CodeBertaCLM
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CodeBertaCLM

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0401
- Accuracy: 0.0151
- F1: 0.0151
- Bleu4: 0.0545

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Bleu4  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| 2.7267        | 1.0   | 1373 | 1.5727          | 0.0161   | 0.0161 | 0.0423 |
| 1.4983        | 2.0   | 2746 | 1.2421          | 0.0170   | 0.0170 | 0.0674 |
| 1.2858        | 3.0   | 4119 | 1.1225          | 0.0154   | 0.0154 | 0.0434 |
| 1.2268        | 4.0   | 5492 | 1.0612          | 0.0153   | 0.0153 | 0.0646 |
| 1.1658        | 5.0   | 6865 | 1.0401          | 0.0151   | 0.0151 | 0.0545 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2