This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the simonycl/Meta-Llama-3-8B-Instruct_metamath-Meta-Llama-3-8B-Instruct-annotate-judge-5 dataset. It achieves the following results on the evaluation set:

Loss: 0.7013
Rewards/chosen: -4.0945
Rewards/rejected: -5.8632
Rewards/accuracies: 0.7060
Rewards/margins: 1.7687
Logps/rejected: -705.5204
Logps/chosen: -502.4185
Logits/rejected: -0.8140
Logits/chosen: -1.0704

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
0.2753	0.7882	400	0.7013	-4.0945	-5.8632	0.7060	1.7687	-705.5204	-502.4185	-0.8140	-1.0704

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-agg-judge

llama-3-8b-instruct-metamath-agg-judge

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

simonycl/
llama-3-8b-instruct-metamath-agg-judge