lambda-llama-3-8b-dpo-test-orca

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lambda-llama-3-8b-dpo-test-orca

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the HuggingFaceH4/ultrafeedback_binarized and the tanliboy/orca_dpo_pairs datasets. It achieves the following results on the evaluation set:

• Loss: 0.4795
• Rewards/chosen: -1.6860
• Rewards/rejected: -2.8132
• Rewards/accuracies: 0.7259
• Rewards/margins: 1.1272
• Logps/rejected: -645.5051
• Logps/chosen: -549.3651
• Logits/rejected: -2.6630
• Logits/chosen: -2.5985

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: 2e-07
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1

Training results

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1