--- 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_60-samples_config-1 results: [] --- # Llama-31-8B_task-1_60-samples_config-1 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 an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.7460 ## 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 | |:-------------:|:-------:|:----:|:---------------:| | 2.1529 | 0.8696 | 5 | 2.0041 | | 1.7276 | 1.9130 | 11 | 1.6163 | | 1.5018 | 2.9565 | 17 | 1.4631 | | 1.3727 | 4.0 | 23 | 1.3338 | | 1.0912 | 4.8696 | 28 | 1.2853 | | 0.8709 | 5.9130 | 34 | 1.2905 | | 0.713 | 6.9565 | 40 | 1.4713 | | 0.4007 | 8.0 | 46 | 1.6719 | | 0.2182 | 8.8696 | 51 | 2.0390 | | 0.0802 | 9.9130 | 57 | 2.5003 | | 0.0304 | 10.9565 | 63 | 2.7328 | | 0.0155 | 12.0 | 69 | 2.7460 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.1.2+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1