| --- |
| license: other |
| tags: |
| - generated_from_trainer |
| base_model: deepseek-ai/deepseek-coder-1.3b-instruct |
| model-index: |
| - name: encoder |
| 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. --> |
|
|
| # encoder |
|
|
| This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-instruct) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0670 |
| - Mse: 1.0575 |
| - Rmse: 1.0283 |
| - Mae: 0.9076 |
|
|
| ## 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: 12 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.01 |
| - num_epochs: 2 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Mse | Rmse | Mae | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:| |
| | 0.0988 | 0.21 | 3000 | 0.0928 | 1.4795 | 1.2164 | 1.1099 | |
| | 0.0793 | 0.42 | 6000 | 0.0867 | 1.4370 | 1.1987 | 1.1076 | |
| | 0.0702 | 0.63 | 9000 | 0.0777 | 0.7554 | 0.8691 | 0.7701 | |
| | 0.0634 | 0.84 | 12000 | 0.0716 | 1.0950 | 1.0464 | 0.9449 | |
| | 0.0563 | 1.05 | 15000 | 0.0686 | 0.9966 | 0.9983 | 0.8899 | |
| | 0.0484 | 1.26 | 18000 | 0.0673 | 1.0653 | 1.0321 | 0.9161 | |
| | 0.0466 | 1.47 | 21000 | 0.0671 | 1.0877 | 1.0429 | 0.9219 | |
| | 0.0462 | 1.68 | 24000 | 0.0670 | 1.0613 | 1.0302 | 0.9090 | |
| | 0.046 | 1.89 | 27000 | 0.0670 | 1.0575 | 1.0283 | 0.9076 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 2.1.0.dev20230605+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
| |
