--- base_model: mistralai/Mistral-Nemo-Instruct-2407 library_name: peft license: other tags: - llama-factory - lora - generated_from_trainer model-index: - name: heat_transfer_sft_5000_mcq_u_1epoch results: [] --- # heat_transfer_sft_5000_mcq_u_1epoch This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the heat_transfer_5000_mcq_u dataset. It achieves the following results on the evaluation set: - Loss: 0.0042 ## 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: 10 - eval_batch_size: 10 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - total_train_batch_size: 20 - total_eval_batch_size: 20 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0075 | 0.2283 | 50 | 0.0059 | | 0.0057 | 0.4566 | 100 | 0.0054 | | 0.0051 | 0.6849 | 150 | 0.0049 | | 0.0043 | 0.9132 | 200 | 0.0042 | ### Framework versions - PEFT 0.12.0 - Transformers 4.46.0 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.20.1