---
library_name: transformers
base_model: microsoft/codebert-base-mlm
tags:
- generated_from_trainer
datasets:
- devgpt-aimotion/the-stack-v2_PlantUML_filtered
metrics:
- accuracy
model-index:
- name: codebert_base_code_uml_c
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: devgpt-aimotion/the-stack-v2_PlantUML_filtered
      type: devgpt-aimotion/the-stack-v2_PlantUML_filtered
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9053223443951083
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# codebert_base_code_uml_c

This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the devgpt-aimotion/the-stack-v2_PlantUML_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4533
- Accuracy: 0.9053

## 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: 0.0001
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use 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: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.5254        | 4.3592 | 10000 | 0.4521          | 0.9053   |


### Framework versions

- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1