zephyr-7b-dpo-full-prometheus-reward-scale-1-rpo

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0240
• Rewards/chosen: -0.1305
• Rewards/rejected: -0.3804
• Rewards/accuracies: 0.7328
• Rewards/margins: 0.2499
• Logps/rejected: -286.3204
• Logps/chosen: -273.0143
• Logits/rejected: -2.4857
• Logits/chosen: -2.5477

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: 8
• eval_batch_size: 8
• seed: 55
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• total_eval_batch_size: 64
• 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	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.0371	0.1143	50	0.0330	0.0162	-0.0844	0.6638	0.1006	-256.7177	-258.3393	-2.5728	-2.6169
0.0326	0.2286	100	0.0284	-0.1604	-0.3762	0.7069	0.2158	-285.9020	-276.0061	-2.2908	-2.3469
0.0276	0.3429	150	0.0261	-0.1426	-0.3607	0.7198	0.2181	-284.3463	-274.2200	-2.3538	-2.3992
0.0257	0.4571	200	0.0255	-0.1250	-0.3457	0.7371	0.2206	-282.8442	-272.4646	-2.4669	-2.5054
0.0259	0.5714	250	0.0249	-0.1421	-0.3761	0.7457	0.2340	-285.8867	-274.1743	-2.5651	-2.6093
0.0244	0.6857	300	0.0244	-0.1115	-0.3601	0.7328	0.2486	-284.2852	-271.1066	-2.4931	-2.5556
0.0232	0.8	350	0.0241	-0.1203	-0.3689	0.7328	0.2486	-285.1674	-271.9947	-2.4940	-2.5542
0.0253	0.9143	400	0.0240	-0.1305	-0.3804	0.7328	0.2499	-286.3204	-273.0143	-2.4857	-2.5477

Framework versions

• Transformers 4.44.0.dev0
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1