library_name, base_model, tags, datasets, model-index

library_name	base_model	tags	datasets	model-index
transformers	W-61/llama-3-8b-base-sft-hh-helpful-8xh200	alignment-handbook beta-dpo generated_from_trainer	Anthropic/hh-rlhf	name results llama-3-8b-base-beta-dpo-hh-helpful-8xh200-20260410-215627

llama-3-8b-base-beta-dpo-hh-helpful-8xh200-20260410-215627

This model is a fine-tuned version of W-61/llama-3-8b-base-sft-hh-helpful-8xh200 on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set:

• Loss: 0.6427
• Beta Dpo/gap Mean: 20.0887
• Beta Dpo/gap Std: 30.0787
• Beta Dpo/beta Used Raw: -0.1169
• Beta Dpo/beta Used: 0.0317
• Beta Dpo/mask Keep Frac: 1.0
• Logits/chosen: -0.6626
• Logits/rejected: -0.6207

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: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 128
• total_eval_batch_size: 128
• 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
0.4098	0.2941	100	0.6251	7.9978	13.2607	0.0159	0.0433	1.0	-0.6978	-0.6669
0.5527	0.5882	200	0.6421	17.1059	25.9459	-0.0801	0.0373	1.0	-0.6983	-0.6587
0.5831	0.8824	300	0.6427	20.0887	30.0787	-0.1169	0.0317	1.0	-0.6626	-0.6207

Framework versions

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