metadata
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
bert_base_code_uml
This model is a fine-tuned version of 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