This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.5372
Rewards/chosen: -1.1911
Rewards/rejected: -2.0021
Rewards/accuracies: 0.7656
Rewards/margins: 0.8110
Logps/rejected: -481.7125
Logps/chosen: -401.6271
Logits/rejected: -0.5622
Logits/chosen: -0.5978

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: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
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
0.5134	0.9984	477	0.5372	-1.1911	-2.0021	0.7656	0.8110	-481.7125	-401.6271	-0.5622	-0.5978

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+rocm6.2
Datasets 3.2.0
Tokenizers 0.20.3

li-muyang/zephyr-8b-dpo-full

zephyr-8b-dpo-full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

li-muyang/
zephyr-8b-dpo-full