--- 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: [] --- [Visualize in Weights & Biases](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