dpo-llama3-8b-grammar-rules

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1500
• Rewards/chosen: -0.7612
• Rewards/rejected: -2.8814
• Rewards/accuracies: 1.0
• Rewards/margins: 2.1202
• Logps/rejected: -647.7891
• Logps/chosen: -291.9149
• Logits/rejected: -1.1894
• Logits/chosen: -1.1810

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-06
• train_batch_size: 1
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.388	0.4444	50	0.3531	-0.2310	-1.1328	1.0	0.9018	-472.9276	-238.8918	-1.2924	-1.2917
0.1309	0.8889	100	0.1500	-0.7612	-2.8814	1.0	2.1202	-647.7891	-291.9149	-1.1894	-1.1810

Framework versions

• PEFT 0.12.0
• Transformers 4.44.0
• Pytorch 2.3.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1