--- license: apache-2.0 base_model: Minbyul/mistral-7b-wo-live_qa-sft tags: - alignment-handbook - trl - dpo - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: mistral-7b-dpo-full-sft-wo-live_qa results: [] --- # mistral-7b-dpo-full-sft-wo-live_qa This model is a fine-tuned version of [Minbyul/mistral-7b-wo-live_qa-sft](https://huggingface.co/Minbyul/mistral-7b-wo-live_qa-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.0469 - Rewards/chosen: -0.7784 - Rewards/rejected: -14.5261 - Rewards/accuracies: 0.875 - Rewards/margins: 13.7477 - Logps/rejected: -2053.0686 - Logps/chosen: -168.4323 - Logits/rejected: -1.5819 - Logits/chosen: -1.9164 ## 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: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - 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 | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.2894 | 0.3 | 100 | 0.2025 | -0.2133 | -2.0069 | 0.875 | 1.7935 | -801.1411 | -111.9223 | -2.6944 | -2.4093 | | 0.1355 | 0.61 | 200 | 0.0506 | -0.8364 | -12.1329 | 0.875 | 11.2965 | -1813.7421 | -174.2286 | -1.5654 | -1.9005 | | 0.0848 | 0.91 | 300 | 0.0468 | -0.7745 | -14.5125 | 0.875 | 13.7379 | -2051.7014 | -168.0429 | -1.5809 | -1.9182 | ### Framework versions - Transformers 4.39.0.dev0 - Pytorch 2.1.2 - Datasets 2.14.6 - Tokenizers 0.15.2