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

Loss: 0.4834
Rewards/chosen: -2.9573
Rewards/rejected: -4.4536
Rewards/accuracies: 0.7760
Rewards/margins: 1.4963
Logps/rejected: -597.7948
Logps/chosen: -448.3257
Logits/rejected: -0.6484
Logits/chosen: -0.6989

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: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 32
total_train_batch_size: 128
total_eval_batch_size: 4
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
0.5062	0.8529	400	0.4834	-2.9573	-4.4536	0.7760	1.4963	-597.7948	-448.3257	-0.6484	-0.6989

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

simonycl/llama-3-8b-instruct-armorm-judge

llama-3-8b-instruct-armorm-judge

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

simonycl/
llama-3-8b-instruct-armorm-judge