metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: CodeBertaCLM
results: []
CodeBertaCLM
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: 0.0068
- Accuracy: 0.0126
- F1: 0.0126
- Bleu4: 0.0363
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Bleu4 |
|---|---|---|---|---|---|---|
| 2.6008 | 1.0 | 687 | 0.0221 | 0.0173 | 0.0173 | 0.1220 |
| 0.0455 | 2.0 | 1374 | 0.0171 | 0.0233 | 0.0233 | 0.1751 |
| 0.0199 | 3.0 | 2061 | 0.0163 | 0.0154 | 0.0154 | 0.0993 |
| 0.0119 | 4.0 | 2748 | 0.0068 | 0.0198 | 0.0198 | 0.1486 |
| 0.0086 | 5.0 | 3435 | 0.0068 | 0.0126 | 0.0126 | 0.0363 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2