llama-3-8b-instruct-gapo-v2-bert-f1-beta10-gamma0.3-lr1.0e-6-1minus-rerun

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: 1.3036
• Rewards/chosen: -16.3155
• Rewards/rejected: -21.8422
• Rewards/accuracies: 0.8313
• Rewards/margins: 5.5267
• Logps/rejected: -2.1842
• Logps/chosen: -1.6315
• Logits/rejected: -1.4149
• Logits/chosen: -1.4050

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
1.2352	0.8550	400	1.3036	-16.3155	-21.8422	0.8313	5.5267	-2.1842	-1.6315	-1.4149	-1.4050

Framework versions

• Transformers 4.44.2
• Pytorch 2.2.0
• Datasets 2.21.0
• Tokenizers 0.19.1