This model is a fine-tuned version of Minbyul/biomistral-7b-wo-medication_qa-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.4656
Rewards/chosen: -0.5066
Rewards/rejected: -1.3382
Rewards/accuracies: 0.75
Rewards/margins: 0.8316
Logps/rejected: -693.0344
Logps/chosen: -456.7123
Logits/rejected: -4.0821
Logits/chosen: -4.1231

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
0.1232	0.83	100	-4.1247	-4.0843	-456.2566	-691.8618	0.4671	0.75	-0.5020	0.8245	-1.3265

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2

Minbyul/biomistral-7b-dpo-full-sft-wo-medication_qa

biomistral-7b-dpo-full-sft-wo-medication_qa

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Minbyul/
biomistral-7b-dpo-full-sft-wo-medication_qa