llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.4

• Loss: 0.5983
• Fcm Dpo/beta: 0.0027
• Margin Dpo/margin Mean: 105.4011
• Margin Dpo/margin Std: 182.7466
• Logps/chosen: -546.8945
• Logps/rejected: -631.3989
• Logps/ref Chosen: -287.8268
• Logps/ref Rejected: -266.9300
• Kl/chosen Kl Mean: -259.0677
• Kl/rejected Kl Mean: -364.4689
• Kl/mean: -311.7683
• Kl/std: 162.3682
• Logits/chosen: -0.8539
• Logits/rejected: -0.8364

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