--- library_name: transformers base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200 tags: - alignment-handbook - margin-dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: llama-3-8b-base-margin-dpo-ultrafeedback-8xh200-20260410-155037 results: [] --- # llama-3-8b-base-margin-dpo-ultrafeedback-8xh200-20260410-155037 This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.5358 - Margin Dpo/margin Mean: 72.1584 - Margin Dpo/margin Std: 96.1592 - Logps/chosen: -403.2485 - Logps/rejected: -474.8625 - Logps/ref Chosen: -280.7076 - Logps/ref Rejected: -280.1632 - Logits/chosen: -0.8223 - Logits/rejected: -0.8121 ## 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: 8 - gradient_accumulation_steps: 2 - total_train_batch_size: 128 - total_eval_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:| | 1.0912 | 0.4188 | 200 | 0.5626 | 60.1408 | 83.6690 | -374.4195 | -434.0159 | -280.7076 | -280.1632 | -0.8522 | -0.8391 | | 1.1088 | 0.8377 | 400 | 0.5358 | 72.1584 | 96.1592 | -403.2485 | -474.8625 | -280.7076 | -280.1632 | -0.8223 | -0.8121 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4