---
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: 0.0068
- Accuracy: 0.0126
- F1: 0.0126
- Bleu4: 0.0363

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Bleu4  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| 2.6008        | 1.0   | 687  | 0.0221          | 0.0173   | 0.0173 | 0.1220 |
| 0.0455        | 2.0   | 1374 | 0.0171          | 0.0233   | 0.0233 | 0.1751 |
| 0.0199        | 3.0   | 2061 | 0.0163          | 0.0154   | 0.0154 | 0.0993 |
| 0.0119        | 4.0   | 2748 | 0.0068          | 0.0198   | 0.0198 | 0.1486 |
| 0.0086        | 5.0   | 3435 | 0.0068          | 0.0126   | 0.0126 | 0.0363 |


### Framework versions

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