| | --- |
| | base_model: microsoft/codebert-base-mlm |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: huggingfacecodebert-base-mlm-finetuned-the-stack-bash |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # huggingfacecodebert-base-mlm-finetuned-the-stack-bash |
| |
|
| | This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.8719 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 4 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 100 |
| | - training_steps: 10000 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:-----:|:---------------:| |
| | | 2.8761 | 0.05 | 500 | 3.0629 | |
| | | 2.3622 | 0.1 | 1000 | 2.5288 | |
| | | 2.5797 | 0.15 | 1500 | 2.3437 | |
| | | 2.7985 | 0.2 | 2000 | 2.1884 | |
| | | 2.6333 | 0.25 | 2500 | 2.1099 | |
| | | 2.2955 | 0.3 | 3000 | 2.0732 | |
| | | 2.4228 | 0.35 | 3500 | 2.0343 | |
| | | 2.3224 | 0.4 | 4000 | 2.0015 | |
| | | 2.1669 | 0.45 | 4500 | 1.9659 | |
| | | 1.98 | 0.5 | 5000 | 1.9458 | |
| | | 2.1847 | 0.55 | 5500 | 1.9258 | |
| | | 2.1145 | 0.6 | 6000 | 1.9235 | |
| | | 2.2392 | 0.65 | 6500 | 1.9019 | |
| | | 2.1206 | 0.7 | 7000 | 1.9106 | |
| | | 2.1796 | 0.75 | 7500 | 1.8852 | |
| | | 2.5239 | 0.8 | 8000 | 1.8781 | |
| | | 1.4346 | 0.85 | 8500 | 1.8754 | |
| | | 2.3741 | 0.9 | 9000 | 1.8704 | |
| | | 1.904 | 0.95 | 9500 | 1.8679 | |
| | | 2.4298 | 1.0 | 10000 | 1.8719 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| |
|
