tulu2-7b-cost-UI-both

UI coherence 10k + UI correctness 10k

This model is a fine-tuned version of allenai/tulu-2-7b on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6883
• Rewards/chosen: -0.1974
• Rewards/rejected: -0.2211
• Rewards/accuracies: 0.5370
• Rewards/margins: 0.0236
• Rewards/margins Max: 0.3503
• Rewards/margins Min: -0.2527
• Rewards/margins Std: 0.1981
• Logps/rejected: -356.2906
• Logps/chosen: -363.1418
• Logits/rejected: 0.9920
• Logits/chosen: 0.8393

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: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• 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
• 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
0.2381	1.0	578	0.6883	-0.1974	-0.2211	0.5370	0.0236	0.3503	-0.2527	0.1981	-356.2906	-363.1418	0.9920	0.8393

Framework versions

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