--- 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-irony results: [] --- # llama-3b-irony 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: 0.5817 - Accuracy: 0.7105 - F1: 0.6146 ## 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 | 1.0 | 30 | 1.0633 | 0.5013 | 0.5155 | | No log | 2.0 | 60 | 0.7927 | 0.5982 | 0.5191 | | No log | 3.0 | 90 | 0.6772 | 0.6531 | 0.5763 | | No log | 4.0 | 120 | 0.6298 | 0.6786 | 0.5896 | | No log | 5.0 | 150 | 0.6055 | 0.6964 | 0.6222 | | No log | 6.0 | 180 | 0.5919 | 0.7041 | 0.5842 | | No log | 7.0 | 210 | 0.5895 | 0.7156 | 0.6455 | | No log | 8.0 | 240 | 0.5849 | 0.7066 | 0.6102 | | No log | 9.0 | 270 | 0.5831 | 0.7168 | 0.6172 | | No log | 10.0 | 300 | 0.5817 | 0.7105 | 0.6146 | ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0