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

Loss: 1.3512
Rewards/chosen: -16.2535
Rewards/rejected: -21.8386
Rewards/accuracies: 0.8394
Rewards/margins: 5.5851
Logps/rejected: -2.1839
Logps/chosen: -1.6254
Logits/rejected: -1.4706
Logits/chosen: -1.4609

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: 4
gradient_accumulation_steps: 16
total_train_batch_size: 128
total_eval_batch_size: 16
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
1.1724	0.8550	400	1.3512	-16.2535	-21.8386	0.8394	5.5851	-2.1839	-1.6254	-1.4706	-1.4609

Framework versions

Transformers 4.44.2
Pytorch 2.2.0
Datasets 2.21.0
Tokenizers 0.19.1

Jimmy19991222/llama-3-8b-instruct-gapo-v2-bert_p-beta10-gamma0.3-lr1.0e-6-scale-log

llama-3-8b-instruct-gapo-v2-bert_p-beta10-gamma0.3-lr1.0e-6-scale-log

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Jimmy19991222/
llama-3-8b-instruct-gapo-v2-bert_p-beta10-gamma0.3-lr1.0e-6-scale-log