--- license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags: - alignment-handbook - trl - dpo - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: mistral-7b-dpo-full-wo-kqa_golden-ep3 results: [] --- # mistral-7b-dpo-full-wo-kqa_golden-ep3 This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.2182 - Rewards/chosen: -1.5510 - Rewards/rejected: -6.3512 - Rewards/accuracies: 0.875 - Rewards/margins: 4.8002 - Logps/rejected: -1537.8291 - Logps/chosen: -720.7828 - Logits/rejected: -2.8834 - Logits/chosen: -3.1394 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.1645 | 0.53 | 100 | 0.2503 | -1.6026 | -5.5026 | 0.8313 | 3.9001 | -1452.9772 | -725.9427 | -2.7934 | -3.0544 | ### Framework versions - Transformers 4.39.0.dev0 - Pytorch 2.1.2 - Datasets 2.14.6 - Tokenizers 0.15.2