metadata
library_name: transformers
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpad-v1-entropy-taskA
results: []
gpad-v1-entropy-taskA
This model is a fine-tuned version of microsoft/codebert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0423
- Accuracy: 0.9908
- F1 Macro: 0.9912
- F1 Weighted: 0.9908
- Precision Macro: 0.9921
- Recall Macro: 0.9903
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|---|
| 0.0643 | 1.0 | 7813 | 0.0518 | 0.9881 | 0.9885 | 0.9881 | 0.9920 | 0.9851 |
| 0.0261 | 2.0 | 15626 | 0.0409 | 0.9902 | 0.9906 | 0.9902 | 0.9914 | 0.9897 |
| 0.044 | 3.0 | 23439 | 0.0423 | 0.9908 | 0.9912 | 0.9908 | 0.9921 | 0.9903 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2