--- 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_star0.6 results: [] --- # llama3-8b-base-new-method-s_star0.6 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: 0.5591 - Fcm Dpo/beta: 0.0089 - Margin Dpo/margin Mean: 55.2826 - Margin Dpo/margin Std: 95.3567 - Logps/chosen: -205.2188 - Logps/rejected: -265.1909 - Logps/ref Chosen: -74.8595 - Logps/ref Rejected: -79.5490 - Logits/chosen: 0.7206 - Logits/rejected: 0.6751 ## 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 | |:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:| | 1.0505 | 0.3023 | 200 | 0.5490 | 0.0445 | 12.8367 | 21.5327 | -94.9354 | -112.4616 | -74.8595 | -79.5490 | 0.4353 | 0.3850 | | 1.0738 | 0.6047 | 400 | 0.5614 | 0.0103 | 44.9123 | 77.2791 | -176.5743 | -226.1761 | -74.8595 | -79.5490 | 0.6246 | 0.5775 | | 1.1653 | 0.9070 | 600 | 0.5591 | 0.0089 | 55.2826 | 95.3567 | -205.2188 | -265.1909 | -74.8595 | -79.5490 | 0.7206 | 0.6751 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4