eurus-7b-cost-UC-5e-7

This model is a fine-tuned version of openbmb/Eurus-7b-sft on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6920
• Rewards/chosen: -0.5152
• Rewards/rejected: -0.5522
• Rewards/accuracies: 0.5560
• Rewards/margins: 0.0369
• Rewards/margins Max: 0.5671
• Rewards/margins Min: -0.4943
• Rewards/margins Std: 0.3483
• Logps/rejected: -312.9047
• Logps/chosen: -326.6244
• Logits/rejected: -2.1863
• Logits/chosen: -2.3047

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: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• 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	Rewards/margins Max	Rewards/margins Min	Rewards/margins Std	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.3977	1.0	968	0.6920	-0.5152	-0.5522	0.5560	0.0369	0.5671	-0.4943	0.3483	-312.9047	-326.6244	-2.1863	-2.3047

Framework versions

• PEFT 0.7.1
• Transformers 4.39.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.14.6
• Tokenizers 0.15.2