--- base_model: meta-llama/Meta-Llama-3.1-8B-Instruct datasets: - GaetanMichelet/chat-60_ft_task-2 - GaetanMichelet/chat-120_ft_task-2 - GaetanMichelet/chat-180_ft_task-2 library_name: peft license: llama3.1 tags: - alignment-handbook - trl - sft - generated_from_trainer model-index: - name: Llama-31-8B_task-2_180-samples_config-2_full results: [] --- # Llama-31-8B_task-2_180-samples_config-2_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 GaetanMichelet/chat-60_ft_task-2, the GaetanMichelet/chat-120_ft_task-2 and the GaetanMichelet/chat-180_ft_task-2 datasets. It achieves the following results on the evaluation set: - Loss: 1.0352 ## 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 | |:-------------:|:-------:|:----:|:---------------:| | 1.5563 | 0.9412 | 8 | 1.5577 | | 1.4499 | 2.0 | 17 | 1.4147 | | 1.3435 | 2.9412 | 25 | 1.2968 | | 1.0893 | 4.0 | 34 | 1.1421 | | 1.0304 | 4.9412 | 42 | 1.0948 | | 1.0336 | 6.0 | 51 | 1.0725 | | 1.0393 | 6.9412 | 59 | 1.0579 | | 0.9727 | 8.0 | 68 | 1.0467 | | 0.9068 | 8.9412 | 76 | 1.0394 | | 0.9015 | 10.0 | 85 | 1.0352 | | 0.8647 | 10.9412 | 93 | 1.0374 | | 0.798 | 12.0 | 102 | 1.0530 | | 0.795 | 12.9412 | 110 | 1.0667 | | 0.7562 | 14.0 | 119 | 1.0935 | | 0.6454 | 14.9412 | 127 | 1.1196 | | 0.5665 | 16.0 | 136 | 1.1875 | | 0.565 | 16.9412 | 144 | 1.2294 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1