llama3_l5_best_entropy_1

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

• Loss: 1.9563
• Rewards/chosen: -8.6021
• Rewards/rejected: -13.9123
• Rewards/accuracies: 0.8434
• Rewards/margins: 5.3102
• Logps/rejected: -1.3912
• Logps/chosen: -0.8602
• Logits/rejected: -1.3261
• Logits/chosen: -1.3707
• Semantic Entropy: 0.9091

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: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Semantic Entropy
1.9268	0.8743	400	1.9563	-8.6021	-13.9123	0.8434	5.3102	-1.3912	-0.8602	-1.3261	-1.3707	0.9091

Framework versions

• Transformers 4.44.2
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1