--- base_model: meta-llama/Meta-Llama-3.1-8B-Instruct library_name: peft license: llama3.1 tags: - trl - sft - generated_from_trainer model-index: - name: Llama-31-8B_task-3_180-samples_config-1_full results: [] --- # Llama-31-8B_task-3_180-samples_config-1_full This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4002 ## 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: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 8 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.6392 | 1.0 | 17 | 1.6279 | | 1.4618 | 2.0 | 34 | 1.4343 | | 1.2006 | 3.0 | 51 | 1.2241 | | 1.0799 | 4.0 | 68 | 1.1761 | | 1.0615 | 5.0 | 85 | 1.1524 | | 1.0045 | 6.0 | 102 | 1.1361 | | 0.9831 | 7.0 | 119 | 1.1392 | | 0.8698 | 8.0 | 136 | 1.1567 | | 0.7759 | 9.0 | 153 | 1.1918 | | 0.7296 | 10.0 | 170 | 1.2537 | | 0.6747 | 11.0 | 187 | 1.2852 | | 0.4777 | 12.0 | 204 | 1.3877 | | 0.5052 | 13.0 | 221 | 1.4002 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1