mistral-orpo-mix-b0.05-l1024-pl512-lr5e-7-cosine

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8648
• Rewards/chosen: -0.0405
• Rewards/rejected: -0.0502
• Rewards/accuracies: 0.6458
• Rewards/margins: 0.0097
• Logps/rejected: -1.0036
• Logps/chosen: -0.8096
• Logits/rejected: -2.9146
• Logits/chosen: -2.9040
• Nll Loss: 0.8392
• Log Odds Ratio: -0.6215
• Log Odds Chosen: 0.3802

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: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• lr_scheduler_warmup_steps: 100
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Nll Loss	Log Odds Ratio	Log Odds Chosen
0.9159	1.0	105	0.8794	-0.0421	-0.0499	0.6302	0.0078	-0.9975	-0.8413	-2.8931	-2.8875	0.8561	-0.6429	0.3024
0.8397	2.0	211	0.8612	-0.0404	-0.0495	0.6458	0.0092	-0.9902	-0.8071	-2.8882	-2.8794	0.8366	-0.6257	0.3555
0.7808	2.99	315	0.8648	-0.0405	-0.0502	0.6458	0.0097	-1.0036	-0.8096	-2.9146	-2.9040	0.8392	-0.6215	0.3802

Framework versions

• Transformers 4.39.0
• Pytorch 2.1.1+cu121
• Datasets 2.16.1
• Tokenizers 0.15.2