tulu2-7b-cost-UF-UI-judge13b-5e-7

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: 0.6929
• Rewards/chosen: 0.0029
• Rewards/rejected: 0.0023
• Rewards/accuracies: 0.5365
• Rewards/margins: 0.0006
• Rewards/margins Max: 0.0723
• Rewards/margins Min: -0.0823
• Rewards/margins Std: 0.0504
• Logps/rejected: -318.0156
• Logps/chosen: -337.8507
• Logits/rejected: 0.8998
• Logits/chosen: 0.7298

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: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• 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
0.6604	1.0	1724	0.6929	0.0029	0.0023	0.5365	0.0006	0.0723	-0.0823	0.0504	-318.0156	-337.8507	0.8998	0.7298

Framework versions

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