--- 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: llama3-8b-base-new-method-s_star0.4 results: [] --- # llama3-8b-base-new-method-s_star0.4 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: 0.6075 - Fcm Dpo/beta: 0.0032 - Margin Dpo/margin Mean: 80.9270 - Margin Dpo/margin Std: 168.3527 - Logps/chosen: -278.6199 - Logps/rejected: -364.2365 - Logps/ref Chosen: -74.8595 - Logps/ref Rejected: -79.5490 - Logits/chosen: 0.8914 - Logits/rejected: 0.8742 ## 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 | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:| | 1.0917 | 0.3023 | 200 | 0.5616 | 0.0221 | 20.9587 | 36.0271 | -112.0402 | -137.6885 | -74.8595 | -79.5490 | 0.5290 | 0.4788 | | 1.134 | 0.6047 | 400 | 0.5988 | 0.0047 | 61.8184 | 122.3443 | -231.1051 | -297.6130 | -74.8595 | -79.5490 | 0.7731 | 0.7383 | | 1.242 | 0.9070 | 600 | 0.6075 | 0.0032 | 80.9270 | 168.3527 | -278.6199 | -364.2365 | -74.8595 | -79.5490 | 0.8914 | 0.8742 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4