This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:

Loss: 132.3632
Rewards/chosen: -0.8503
Rewards/rejected: -0.8889
Rewards/accuracies: 0.5040
Rewards/margins: 0.0387
Logps/rejected: -0.3556
Logps/chosen: -0.3401
Logits/rejected: -1.2982
Logits/chosen: -1.3372

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: 1e-06
train_batch_size: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 128
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	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
196.6313	0.8549	400	132.3632	-0.8503	-0.8889	0.5040	0.0387	-0.3556	-0.3401	-1.2982	-1.3372

Framework versions

Transformers 4.41.2
Pytorch 2.2.0
Datasets 2.20.0
Tokenizers 0.19.1

RAY2L/Llama-3-Instruct-8B-SimPOW-0

llama-3-8b-instruct-simpo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RAY2L/
Llama-3-Instruct-8B-SimPOW-0