dpo-selective-buffer-spo-shift

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6777
• Rewards/chosen: -0.1371
• Rewards/rejected: -0.0830
• Rewards/accuracies: 0.4693
• Rewards/margins: -0.0541
• Rewards/safe Rewards: -0.1332
• Rewards/unsafe Rewards: -0.1263
• Logps/rejected: -92.4348
• Logps/chosen: -131.0029
• Logits/rejected: -1.8308
• Logits/chosen: -2.0825

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: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• 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

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Rewards/safe Rewards	Rewards/unsafe Rewards	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
131.6857	0.27	500	0.8894	-0.1023	-0.0129	0.4546	-0.0893	-0.1043	-0.1017	-92.3648	-130.9681	-1.8032	-2.0565
34.7958	0.54	1000	0.7397	-0.1263	-0.1290	0.5028	0.0026	-0.1237	-0.1264	-92.4809	-130.9922	-1.7990	-2.0551
15.9924	0.81	1500	0.6823	-0.1578	-0.1077	0.4713	-0.0501	-0.1557	-0.1535	-92.4596	-131.0237	-1.8335	-2.0849

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.2
• Datasets 2.14.6
• Tokenizers 0.15.2