--- library_name: peft license: llama3.2 base_model: meta-llama/Llama-3.2-1B-Instruct tags: - base_model:adapter:meta-llama/Llama-3.2-1B-Instruct - lora - transformers pipeline_tag: text-generation model-index: - name: Llama3.2-1B-QLoRA-Explainer results: [] --- # Llama3.2-1B-QLoRA-Explainer This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0579 ## 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: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0652 | 0.3556 | 200 | 0.0650 | | 0.0626 | 0.7111 | 400 | 0.0615 | | 0.06 | 1.0658 | 600 | 0.0596 | | 0.0596 | 1.4213 | 800 | 0.0591 | | 0.0588 | 1.7769 | 1000 | 0.0587 | | 0.0582 | 2.1316 | 1200 | 0.0584 | | 0.0581 | 2.4871 | 1400 | 0.0583 | | 0.0576 | 2.8427 | 1600 | 0.0579 | ### Framework versions - PEFT 0.17.0 - Transformers 4.55.2 - Pytorch 2.8.0+cu128 - Datasets 4.0.0 - Tokenizers 0.21.4