---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
datasets:
- devgpt-aimotion/the-stack-v2_PlantUML_filtered
metrics:
- accuracy
model-index:
- name: bert_base_code_uml
  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: 0.829663160408593
---

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

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the devgpt-aimotion/the-stack-v2_PlantUML_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8230
- Accuracy: 0.8297

## 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: 25

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.4929        | 7.8493  | 10000 | 2.1514          | 0.5692   |
| 0.9263        | 15.6986 | 20000 | 0.9068          | 0.8143   |
| 0.8293        | 23.5479 | 30000 | 0.8292          | 0.8286   |


### Framework versions

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