--- # sft_iteration_0 This model is a fine-tuned version of [/home/wentaos/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a](https://huggingface.co//home/wentaos/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a) on the /data/group_data/cx_group/MCTS-agent/my_datasets/math_sft_dpo_DI/sft/iteration_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.7719 ## 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: 1e-06 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - total_eval_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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.5289 | 0.9988 | 217 | 0.5940 | | 0.4472 | 1.9977 | 434 | 0.6037 | | 0.2872 | 2.9965 | 651 | 0.6949 | | 0.2589 | 3.9954 | 868 | 0.7719 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.3.1+cu121 - Datasets 3.0.2 - Tokenizers 0.19.1