metadata
library_name: transformers
base_model: microsoft/CodeGPT-small-java
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: microsoft_CodeGPT-small-java_1_ft_clm
results: []
microsoft_CodeGPT-small-java_1_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: 1.2841
- Accuracy: 0.7565
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: 8
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.6967 | 0.5028 | 500 | 1.3162 | 0.7521 |
| 0.6481 | 1.0050 | 1000 | 1.3002 | 0.7551 |
| 0.6091 | 1.5078 | 1500 | 1.2965 | 0.7550 |
| 0.6091 | 2.0101 | 2000 | 1.2894 | 0.7556 |
| 0.5805 | 2.5128 | 2500 | 1.2918 | 0.7556 |
| 0.557 | 3.0151 | 3000 | 1.2862 | 0.7559 |
| 0.5513 | 3.5178 | 3500 | 1.2841 | 0.7565 |
| 0.5468 | 4.0201 | 4000 | 1.2849 | 0.7562 |
| 0.5513 | 4.5229 | 4500 | 1.2895 | 0.7559 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2