--- base_model: mistralai/Mistral-7B-v0.1 tags: - alignment-handbook - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: mistral_7b_gsm8k_ep2_1e-5_dpo results: [] --- [Visualize in Weights & Biases](https://wandb.ai/hbin0701/DPO/runs/8aboqbe6) # mistral_7b_gsm8k_ep2_1e-5_dpo This model is a fine-tuned version of [/home/hyeonbin/self_train/Verifiers/models/mistral_7b_gsm8k_ep2_1e-5_rft_round1](https://huggingface.co//home/hyeonbin/self_train/Verifiers/models/mistral_7b_gsm8k_ep2_1e-5_rft_round1) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.0005 - Rewards/chosen: -1.7120 - Rewards/rejected: -14.3548 - Rewards/accuracies: 1.0 - Rewards/margins: 12.6428 - Logps/rejected: -1466.6733 - Logps/chosen: -208.2280 - Logits/rejected: -3.2168 - Logits/chosen: -2.3996 ## 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-07 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 32 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.014 | 1.0 | 7066 | 0.0005 | -1.7120 | -14.3548 | 1.0 | 12.6428 | -1466.6733 | -208.2280 | -3.2168 | -2.3996 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.14.6 - Tokenizers 0.19.1