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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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