Llama-3.1-8B-Magpie-Mix-RC-UltraDPO-08

This model is a fine-tuned version of Magpie-Align/Llama-3-1-8B-Magpie-Mix-300KMT-150KR-200KC on the flydust/llama3-ultrafeedback-armorm-2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3828
• Rewards/chosen: -4.2186
• Rewards/rejected: -5.8751
• Rewards/accuracies: 0.8476
• Rewards/margins: 1.6565
• Logps/rejected: -837.7465
• Logps/chosen: -675.1885
• Logits/rejected: -0.4098
• Logits/chosen: -0.3798

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: 8e-07
• 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
0.5697	0.2138	100	0.5157	-2.7203	-3.5480	0.7317	0.8277	-605.0303	-525.3530	-0.3811	-0.3571
0.517	0.4275	200	0.4364	-3.3924	-4.6257	0.8110	1.2333	-712.8077	-592.5715	-0.3439	-0.3156
0.3774	0.6413	300	0.3968	-3.9322	-5.4972	0.8455	1.5650	-799.9586	-646.5525	-0.4006	-0.3705
0.399	0.8550	400	0.3845	-4.0703	-5.6702	0.8476	1.5999	-817.2530	-660.3575	-0.4061	-0.3760

Framework versions

• Transformers 4.43.2
• Pytorch 2.4.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1