llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.5-s_star-0.45-20260429-032138

• Loss: 0.5558
• Fcm Dpo/beta: 0.0120
• Margin Dpo/margin Mean: 39.2189
• Margin Dpo/margin Std: 59.5473
• Logps/chosen: -336.5880
• Logps/rejected: -354.9101
• Logps/ref Chosen: -287.8268
• Logps/ref Rejected: -266.9300
• Kl/chosen Kl Mean: -48.7612
• Kl/rejected Kl Mean: -87.9800
• Kl/mean: -68.3706
• Kl/std: 53.9070
• Logits/chosen: -0.8206
• Logits/rejected: -0.8117

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 5e-07
• train_batch_size: 4
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 8
• 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

Framework versions

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