| | --- |
| | base_model: huggingface/CodeBERTa-small-v1 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: huggingfaceCodeBerta-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. --> |
| |
|
| | # huggingfaceCodeBerta-finetuned-the-stack-bash |
| |
|
| | This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.4191 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:| |
| | | 3.3233 | 0.05 | 500 | 3.4143 | |
| | | 3.2135 | 0.1 | 1000 | 3.0184 | |
| | | 3.1977 | 0.15 | 1500 | 2.8537 | |
| | | 2.9303 | 0.2 | 2000 | 2.7396 | |
| | | 3.1618 | 0.25 | 2500 | 2.6954 | |
| | | 2.9122 | 0.3 | 3000 | 2.6338 | |
| | | 2.8965 | 0.35 | 3500 | 2.5881 | |
| | | 2.599 | 0.4 | 4000 | 2.5677 | |
| | | 2.8213 | 0.45 | 4500 | 2.5247 | |
| | | 2.516 | 0.5 | 5000 | 2.5118 | |
| | | 2.8975 | 0.55 | 5500 | 2.4817 | |
| | | 2.3503 | 0.6 | 6000 | 2.4803 | |
| | | 2.1736 | 0.65 | 6500 | 2.4650 | |
| | | 2.8777 | 0.7 | 7000 | 2.4394 | |
| | | 2.5809 | 0.75 | 7500 | 2.4391 | |
| | | 2.6986 | 0.8 | 8000 | 2.4199 | |
| | | 3.2199 | 0.85 | 8500 | 2.4354 | |
| | | 2.3214 | 0.9 | 9000 | 2.4174 | |
| | | 0.7788 | 0.95 | 9500 | 2.4156 | |
| | | 2.6361 | 1.0 | 10000 | 2.4191 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| |
|
