---
library_name: transformers
base_model: microsoft/CodeGPT-small-java
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: microsoft_CodeGPT-small-java_0_ft_clm
  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. -->

# microsoft_CodeGPT-small-java_0_ft_clm

This model is a fine-tuned version of [microsoft/CodeGPT-small-java](https://huggingface.co/microsoft/CodeGPT-small-java) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1672
- Accuracy: 0.7708

## 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: 8e-05
- train_batch_size: 4
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 24
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8842        | 0.7788 | 500  | 1.1934          | 0.7688   |
| 0.7557        | 1.5576 | 1000 | 1.1676          | 0.7693   |
| 0.7033        | 2.3364 | 1500 | 1.1631          | 0.7705   |
| 0.6624        | 3.1153 | 2000 | 1.1650          | 0.7707   |
| 0.6414        | 3.8941 | 2500 | 1.1646          | 0.7710   |
| 0.6187        | 4.6729 | 3000 | 1.1672          | 0.7708   |


### Framework versions

- Transformers 4.53.0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2