---
library_name: transformers
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpad-v1-entropy-taskA
  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. -->

# gpad-v1-entropy-taskA

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: 0.0423
- Accuracy: 0.9908
- F1 Macro: 0.9912
- F1 Weighted: 0.9908
- Precision Macro: 0.9921
- Recall Macro: 0.9903

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|
| 0.0643        | 1.0   | 7813  | 0.0518          | 0.9881   | 0.9885   | 0.9881      | 0.9920          | 0.9851       |
| 0.0261        | 2.0   | 15626 | 0.0409          | 0.9902   | 0.9906   | 0.9902      | 0.9914          | 0.9897       |
| 0.044         | 3.0   | 23439 | 0.0423          | 0.9908   | 0.9912   | 0.9908      | 0.9921          | 0.9903       |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2