metadata
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: []
microsoft_CodeGPT-small-java_0_ft_clm
This model is a fine-tuned version of 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