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