--- library_name: transformers base_model: jackf857/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452 tags: - alignment-handbook - beta-dpo - generated_from_trainer datasets: - Anthropic/hh-rlhf model-index: - name: qwen3-8b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260424-025105 results: [] --- # qwen3-8b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260424-025105 This model is a fine-tuned version of [jackf857/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452](https://huggingface.co/jackf857/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452) on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set: - Loss: 0.7256 - Beta Dpo/gap Mean: 9.9202 - Beta Dpo/gap Std: 18.3470 - Beta Dpo/beta Used Raw: 0.1809 - Beta Dpo/beta Used: 0.1995 - Beta Dpo/mask Keep Frac: 1.0 - Logits/chosen: 1.5449 - Logits/rejected: 1.4137 ## 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 | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:| | 1.3382 | 0.1512 | 100 | 0.6596 | 0.5103 | 1.3374 | 0.1093 | 0.1093 | 1.0 | 1.8052 | 1.6946 | | 1.0452 | 0.3023 | 200 | 0.6042 | 5.1820 | 10.9635 | 0.1250 | 0.1302 | 1.0 | 1.6393 | 1.5121 | | 1.1502 | 0.4535 | 300 | 0.6283 | 8.5454 | 15.3857 | 0.1243 | 0.1420 | 1.0 | 1.4622 | 1.3384 | | 1.3806 | 0.6047 | 400 | 0.6464 | 9.9655 | 16.5703 | 0.1189 | 0.1405 | 1.0 | 1.4474 | 1.3215 | | 1.3396 | 0.7559 | 500 | 0.6756 | 11.0204 | 19.5206 | 0.1269 | 0.1533 | 1.0 | 1.3984 | 1.2735 | | 1.0636 | 0.9070 | 600 | 0.7256 | 9.9202 | 18.3470 | 0.1809 | 0.1995 | 1.0 | 1.5449 | 1.4137 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4