--- base_model: microsoft/Phi-3-mini-4k-instruct library_name: peft license: mit tags: - trl - sft - generated_from_trainer model-index: - name: phi-3-mini-LoRA results: [] --- [Visualize in Weights & Biases](https://wandb.ai/medvediev_company/Phi3-mini-ft-python-code/runs/sq01a78h) # phi-3-mini-LoRA 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: 0.7929 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-------:|:----:|:---------------:| | 1.0549 | 17.3913 | 100 | 0.7929 | ### Framework versions - PEFT 0.11.1 - Transformers 4.42.3 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1