library_name, base_model, tags, datasets, model-index

library_name	base_model	tags	datasets	model-index
transformers	jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452	alignment-handbook beta-dpo generated_from_trainer	Anthropic/hh-rlhf	name results qwen3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260424-013732

qwen3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260424-013732

This model is a fine-tuned version of jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452 on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set:

• Loss: 0.6505
• Beta Dpo/gap Mean: 25.7183
• Beta Dpo/gap Std: 26.1829
• Beta Dpo/beta Used Raw: -0.2537
• Beta Dpo/beta Used: 0.0212
• Beta Dpo/mask Keep Frac: 1.0
• Logits/chosen: -1.6123
• Logits/rejected: -1.2796

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
1.1246	0.1468	100	0.6499	4.6173	6.2353	-0.0000	0.0293	1.0	-0.1879	0.0487
0.313	0.2937	200	0.6346	12.9809	14.5981	-0.0999	0.0229	1.0	-1.1708	-0.8922
0.6858	0.4405	300	0.6556	19.2389	20.8328	-0.2038	0.0146	1.0	-1.4133	-1.1126
0.7246	0.5874	400	0.6605	25.6196	25.0584	-0.3654	0.0094	1.0	-1.5698	-1.2495
0.9705	0.7342	500	0.6340	24.0392	26.5263	-0.1783	0.0322	1.0	-1.7312	-1.4078
0.8177	0.8811	600	0.6505	25.7183	26.1829	-0.2537	0.0212	1.0	-1.6123	-1.2796

Framework versions

• Transformers 4.51.0
• Pytorch 2.3.1+cu121
• Datasets 2.21.0
• Tokenizers 0.21.4