tulu2-13b-cost-UF-5e-7

This model is a fine-tuned version of allenai/tulu-2-13b on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6933
• Rewards/chosen: 0.0268
• Rewards/rejected: 0.0265
• Rewards/accuracies: 0.5360
• Rewards/margins: 0.0002
• Rewards/margins Max: 0.0601
• Rewards/margins Min: -0.0619
• Rewards/margins Std: 0.0406
• Logps/rejected: -327.5517
• Logps/chosen: -331.2336
• Logits/rejected: -0.8962
• Logits/chosen: -1.0222

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
0.6665	1.0	927	0.6933	0.0268	0.0265	0.5360	0.0002	0.0601	-0.0619	0.0406	-327.5517	-331.2336	-0.8962	-1.0222

Framework versions

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