MrezaPRZ/sql-encoder

1---2license: other3tags:4- generated_from_trainer5base_model: deepseek-ai/deepseek-coder-1.3b-instruct6model-index:7- name: encoder8  results: []9---10 11<!-- This model card has been generated automatically according to the information the Trainer had access to. You12should probably proofread and complete it, then remove this comment. -->13 14# encoder15 16This 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.17It achieves the following results on the evaluation set:18- Loss: 0.067019- Mse: 1.057520- Rmse: 1.028321- Mae: 0.907622 23## Model description24 25More information needed26 27## Intended uses & limitations28 29More information needed30 31## Training and evaluation data32 33More information needed34 35## Training procedure36 37### Training hyperparameters38 39The following hyperparameters were used during training:40- learning_rate: 5e-0541- train_batch_size: 1242- eval_batch_size: 843- seed: 4244- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0845- lr_scheduler_type: cosine46- lr_scheduler_warmup_ratio: 0.0147- num_epochs: 248 49### Training results50 51| Training Loss | Epoch | Step  | Validation Loss | Mse    | Rmse   | Mae    |52|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|53| 0.0988        | 0.21  | 3000  | 0.0928          | 1.4795 | 1.2164 | 1.1099 |54| 0.0793        | 0.42  | 6000  | 0.0867          | 1.4370 | 1.1987 | 1.1076 |55| 0.0702        | 0.63  | 9000  | 0.0777          | 0.7554 | 0.8691 | 0.7701 |56| 0.0634        | 0.84  | 12000 | 0.0716          | 1.0950 | 1.0464 | 0.9449 |57| 0.0563        | 1.05  | 15000 | 0.0686          | 0.9966 | 0.9983 | 0.8899 |58| 0.0484        | 1.26  | 18000 | 0.0673          | 1.0653 | 1.0321 | 0.9161 |59| 0.0466        | 1.47  | 21000 | 0.0671          | 1.0877 | 1.0429 | 0.9219 |60| 0.0462        | 1.68  | 24000 | 0.0670          | 1.0613 | 1.0302 | 0.9090 |61| 0.046         | 1.89  | 27000 | 0.0670          | 1.0575 | 1.0283 | 0.9076 |62 63 64### Framework versions65 66- Transformers 4.37.267- Pytorch 2.1.0.dev20230605+cu12168- Datasets 2.17.069- Tokenizers 0.15.270