--- base_model: meta-llama/Meta-Llama-3.1-8B-Instruct datasets: - hansh/hansken_hql library_name: peft license: llama3.1 tags: - alignment-handbook - trl - sft - generated_from_trainer model-index: - name: hansken_human_hql results: [] --- # hansken_human_hql 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 hansh/hansken_hql dataset. It achieves the following results on the evaluation set: - Loss: 0.2362 ## 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: 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: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.4508 | 0.9976 | 102 | 0.4433 | | 0.302 | 1.9951 | 204 | 0.3140 | | 0.2692 | 2.9927 | 306 | 0.2616 | | 0.177 | 4.0 | 409 | 0.2431 | | 0.1616 | 4.9976 | 511 | 0.2362 | | 0.1358 | 5.9951 | 613 | 0.2394 | | 0.1199 | 6.9927 | 715 | 0.2474 | | 0.1051 | 8.0 | 818 | 0.2625 | | 0.0945 | 8.9976 | 920 | 0.2797 | | 0.0843 | 9.9951 | 1022 | 0.2892 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1