--- library_name: peft license: llama3.2 base_model: meta-llama/Llama-3.2-3B-Instruct tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: llama-3b-offense results: [] --- # llama-3b-offense This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5348 - Accuracy: 0.7547 - F1: 0.4462 ## 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: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Use adamw_torch 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: 100 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| | No log | 0.9662 | 100 | 0.6581 | 0.6802 | 0.3560 | | No log | 1.9275 | 200 | 0.5982 | 0.7105 | 0.4276 | | No log | 2.8889 | 300 | 0.5637 | 0.7349 | 0.4466 | | No log | 3.8502 | 400 | 0.5506 | 0.7349 | 0.4356 | | 2.3869 | 4.8116 | 500 | 0.5452 | 0.75 | 0.4769 | | 2.3869 | 5.7729 | 600 | 0.5400 | 0.7535 | 0.4619 | | 2.3869 | 6.7343 | 700 | 0.5322 | 0.7593 | 0.5036 | | 2.3869 | 7.6957 | 800 | 0.5339 | 0.7570 | 0.4709 | | 2.3869 | 8.6570 | 900 | 0.5316 | 0.7616 | 0.4888 | | 1.9359 | 9.6184 | 1000 | 0.5348 | 0.7547 | 0.4462 | ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0