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

Loss: 0.1754
Rewards/chosen: -4.0084
Rewards/rejected: -10.7133
Rewards/accuracies: 0.9260
Rewards/margins: 6.7050
Logps/rejected: -1190.5024
Logps/chosen: -493.8166
Logits/rejected: -0.1943
Logits/chosen: -0.5449

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: 2
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 32
total_train_batch_size: 128
total_eval_batch_size: 8
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
0.1771	0.7881	400	0.1754	-4.0084	-10.7133	0.9260	6.7050	-1190.5024	-493.8166	-0.1943	-0.5449

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

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

llama-3-8b-instruct-metamath-armorm

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

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