--- 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-1_180-samples_config-2_full_auto results: [] --- # Llama-31-8B_task-1_180-samples_config-2_full_auto 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: 1.2316 ## 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: 16 - total_train_batch_size: 16 - 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 | |:-------------:|:-------:|:----:|:---------------:| | 2.1079 | 0.9412 | 8 | 2.0439 | | 1.7735 | 2.0 | 17 | 1.6643 | | 1.4106 | 2.9412 | 25 | 1.2322 | | 0.901 | 4.0 | 34 | 0.9259 | | 0.8657 | 4.9412 | 42 | 0.8770 | | 0.846 | 6.0 | 51 | 0.8422 | | 0.7582 | 6.9412 | 59 | 0.8153 | | 0.7203 | 8.0 | 68 | 0.7906 | | 0.6598 | 8.9412 | 76 | 0.7848 | | 0.5979 | 10.0 | 85 | 0.7954 | | 0.5547 | 10.9412 | 93 | 0.8095 | | 0.4007 | 12.0 | 102 | 0.8623 | | 0.3489 | 12.9412 | 110 | 0.9627 | | 0.2894 | 14.0 | 119 | 1.0531 | | 0.1972 | 14.9412 | 127 | 1.1217 | | 0.1682 | 16.0 | 136 | 1.2316 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1