--- license: other base_model: HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 tags: - alignment-handbook - trl - dpo - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - argilla/dpo-mix-7k model-index: - name: zephyr-7b-gemma-dpo results: [] --- [Visualize in Weights & Biases](https://wandb.ai/kirill-fedyanin/huggingface/runs/uj2to373) # zephyr-7b-gemma-dpo This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-gemma-sft-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-sft-v0.1) on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set: - Loss: 0.4658 - Rewards/chosen: -4.1134 - Rewards/rejected: -5.8777 - Rewards/accuracies: 0.7292 - Rewards/margins: 1.7644 - Logps/rejected: -479.6258 - Logps/chosen: -445.9359 - Logits/rejected: 85.7594 - Logits/chosen: 91.4868 ## 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: 2 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - 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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.1497 | 1.8957 | 100 | 0.4608 | -4.1286 | -5.8457 | 0.7292 | 1.7171 | -478.9854 | -446.2400 | 85.7808 | 91.4893 | ### Framework versions - Transformers 4.41.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1