| | --- |
| | base_model: microsoft/Phi-3-mini-4k-instruct |
| | library_name: peft |
| | license: mit |
| | tags: |
| | - trl |
| | - sft |
| | - generated_from_trainer |
| | model-index: |
| | - name: phi-3-text2sql-ssh |
| | 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. --> |
| |
|
| | [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/truskovskiyk/gpu-jobs-comparison/runs/cf8rtqag) |
| | # phi-3-text2sql-ssh |
| |
|
| | This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7745 |
| |
|
| | ## 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: 0.0001 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | No log | 0 | 0 | 2.8774 | |
| | | 1.3552 | 0.1072 | 500 | 0.8898 | |
| | | 0.8559 | 0.2143 | 1000 | 0.8311 | |
| | | 0.8152 | 0.3215 | 1500 | 0.8096 | |
| | | 0.7986 | 0.4287 | 2000 | 0.7940 | |
| | | 0.7901 | 0.5358 | 2500 | 0.7866 | |
| | | 0.7876 | 0.6430 | 3000 | 0.7806 | |
| | | 0.7806 | 0.7502 | 3500 | 0.7767 | |
| | | 0.7729 | 0.8574 | 4000 | 0.7751 | |
| | | 0.7735 | 0.9645 | 4500 | 0.7745 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.11.1 |
| | - Transformers 4.42.3 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.19.1 |
