--- library_name: peft tags: - alignment-handbook - generated_from_trainer # base_model: /ML-A100/team/mm/zhangge/iterativeDPO/data/model/full/neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3 # datasets: # - /ML-A100/team/mm/zhangge/iterativeDPO/data/dataset/generate/neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3-generate-chosen-rejected-reward model-index: - name: neo_7B_sft_v0_1_plus-dpo-iter2-beta0_05 results: [] --- # neo_7B_sft_v0_1_plus-dpo-iter2-beta0_05 This model is a fine-tuned version of [/ML-A100/team/mm/zhangge/iterativeDPO/data/model/full/neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3](https://huggingface.co//ML-A100/team/mm/zhangge/iterativeDPO/data/model/full/neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3) on the /ML-A100/team/mm/zhangge/iterativeDPO/data/dataset/generate/neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3-generate-chosen-rejected-reward dataset. ## 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: 3 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 128 - total_train_batch_size: 384 - total_eval_batch_size: 1024 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1 ### Training results ### Framework versions - PEFT 0.7.1 - Transformers 4.39.0.dev0 - Pytorch 2.3.0+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2