--- license: other base_model: lewtun/gemma-7b-sft-full-ultrachat-v0 tags: - alignment-handbook - trl - dpo - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - HuggingFaceH4/orca_dpo_pairs model-index: - name: gemma-7b-dpo-full-orca-v0 results: [] --- # gemma-7b-dpo-full-orca-v0 This model is a fine-tuned version of [lewtun/gemma-7b-sft-full-ultrachat-v0](https://huggingface.co./lewtun/gemma-7b-sft-full-ultrachat-v0) on the HuggingFaceH4/orca_dpo_pairs dataset. It achieves the following results on the evaluation set: - Loss: 0.0131 - Rewards/chosen: 4.5525 - Rewards/rejected: -7.7149 - Rewards/accuracies: 0.9922 - Rewards/margins: 12.2674 - Logps/rejected: -860.7157 - Logps/chosen: -725.1588 - Logits/rejected: 141.1811 - Logits/chosen: 94.1054 ## 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-07 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - total_eval_batch_size: 32 - 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 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1