phi_3-offline-dpo-noise-0.0-42

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6938
• Rewards/chosen: -0.0001
• Rewards/rejected: -0.0001
• Rewards/accuracies: 0.5357
• Rewards/margins: 0.0000
• Logps/rejected: -395.4152
• Logps/chosen: -396.9144
• Logits/rejected: 12.8496
• Logits/chosen: 13.9987

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-06
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• total_eval_batch_size: 16
• 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

• PEFT 0.7.1
• Transformers 4.42.3
• Pytorch 2.3.0+cu121
• Datasets 2.14.6
• Tokenizers 0.19.1