This model is a fine-tuned version of dmis-lab/selfbiorag_7b on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.6669
Rewards/chosen: 0.0740
Rewards/rejected: 0.0190
Rewards/accuracies: 0.6977
Rewards/margins: 0.0550
Logps/rejected: -170.3629
Logps/chosen: -158.5215
Logits/rejected: -1.6515
Logits/chosen: -1.6773

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: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 64
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

Training Loss	Epoch	Step	Logits/chosen	Logits/rejected	Logps/chosen	Logps/rejected	Validation Loss	Rewards/accuracies	Rewards/chosen	Rewards/margins	Rewards/rejected
0.6508	0.61	100	-1.6968	-1.6723	-158.8701	-170.2428	0.6691	0.6941	0.0706	0.0503	0.0202

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2

Minbyul/selfbiorag-7b-dpo-full-wo-healthsearch_qa-ep3

selfbiorag-7b-dpo-full-wo-healthsearch_qa-ep3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Minbyul/
selfbiorag-7b-dpo-full-wo-healthsearch_qa-ep3