--- library_name: transformers base_model: W-61/llama-3-8b-base-sft-hh-harmless-4xh200 tags: - alignment-handbook - new-dpo - generated_from_trainer datasets: - Anthropic/hh-rlhf model-index: - name: llama-3-8b-base-new-dpo-hh-harmless-s_star0.6-4xh200-batch-64-20260421-213851 results: [] --- # llama-3-8b-base-new-dpo-hh-harmless-s_star0.6-4xh200-batch-64-20260421-213851 This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-harmless-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-harmless-4xh200) on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set: - Loss: 0.5427 - Fcm Dpo/beta: 0.0127 - Fcm Dpo/q T: 0.3797 - Fcm Dpo/delta: -0.0085 - Fcm Dpo/margin: 46.9651 - Margin Dpo/margin Mean: 46.9651 - Margin Dpo/margin Std: 76.4295 - Logps/chosen: -176.9747 - Logps/rejected: -228.6294 - Logps/ref Chosen: -74.8595 - Logps/ref Rejected: -79.5490 - Logits/chosen: 0.6471 - Logits/rejected: 0.5976 ## 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: 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 | Fcm Dpo/beta | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:------------:|:-----------:|:-------------:|:--------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:| | 1.0309 | 0.3023 | 200 | 0.5479 | 0.0706 | 0.3810 | -0.0076 | 8.4404 | 8.4404 | 14.1426 | -88.2471 | -101.3770 | -74.8595 | -79.5490 | 0.3430 | 0.2953 | | 1.058 | 0.6047 | 400 | 0.5442 | 0.0156 | 0.3824 | 0.0052 | 37.3081 | 37.3081 | 61.1427 | -151.6879 | -193.6855 | -74.8595 | -79.5490 | 0.6412 | 0.5884 | | 1.1526 | 0.9070 | 600 | 0.5427 | 0.0127 | 0.3797 | -0.0085 | 46.9651 | 46.9651 | 76.4295 | -176.9747 | -228.6294 | -74.8595 | -79.5490 | 0.6471 | 0.5976 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4