--- base_model: meta-llama/Llama-3.1-8B-Instruct library_name: peft license: llama3.1 tags: - llama-factory - lora - generated_from_trainer model-index: - name: Llama-3.1-8B-Instruct-SFT-900 results: [] --- # Llama-3.1-8B-Instruct-SFT-900 This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the bct_non_cot_sft_900 dataset. It achieves the following results on the evaluation set: - Loss: 0.1053 ## 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: 5e-06 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - 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: 10.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.201 | 0.9877 | 50 | 1.0016 | | 0.1407 | 1.9753 | 100 | 0.1513 | | 0.0885 | 2.9630 | 150 | 0.1082 | | 0.0743 | 3.9506 | 200 | 0.1068 | | 0.0855 | 4.9383 | 250 | 0.1062 | | 0.0571 | 5.9259 | 300 | 0.1058 | | 0.063 | 6.9136 | 350 | 0.1054 | | 0.0597 | 7.9012 | 400 | 0.1057 | | 0.0694 | 8.8889 | 450 | 0.1053 | | 0.0593 | 9.8765 | 500 | 0.1053 | ### Framework versions - PEFT 0.12.0 - Transformers 4.45.2 - Pytorch 2.3.0 - Datasets 2.19.0 - Tokenizers 0.20.0