---
library_name: transformers
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3489
- Accuracy: 0.8556
- F1: 0.9020
- Precision: 0.8502
- Recall: 0.9606

## 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: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 192
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 16   | 0.5511          | 0.6921   | 0.8180 | 0.6921    | 1.0    |
| No log        | 2.0   | 32   | 0.4566          | 0.7793   | 0.8439 | 0.8264    | 0.8622 |
| No log        | 3.0   | 48   | 0.4230          | 0.8093   | 0.8611 | 0.868     | 0.8543 |
| No log        | 4.0   | 64   | 0.3796          | 0.8610   | 0.9061 | 0.8512    | 0.9685 |
| No log        | 5.0   | 80   | 0.3521          | 0.8583   | 0.9019 | 0.8659    | 0.9409 |
| No log        | 6.0   | 96   | 0.3509          | 0.8556   | 0.8990 | 0.8708    | 0.9291 |
| No log        | 7.0   | 112  | 0.3489          | 0.8556   | 0.9020 | 0.8502    | 0.9606 |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2