--- library_name: peft license: llama3 base_model: meta-llama/Meta-Llama-3-8B-Instruct tags: - llama-factory - lora - generated_from_trainer model-index: - name: lora_all results: [] --- # lora_all This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the healthcaremagic dataset. It achieves the following results on the evaluation set: - Loss: 1.7827 ## 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: 5e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - total_train_batch_size: 256 - total_eval_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.6961 | 2.8439 | 1000 | 1.7828 | ### Framework versions - PEFT 0.12.0 - Transformers 4.46.1 - Pytorch 2.5.1 - Datasets 3.1.0 - Tokenizers 0.20.3