nash_ave_pi_with_golden_iter_3

This model is a fine-tuned version of YYYYYYibo/nash_ave_pi_with_golden_iter_2 on the updated and the original datasets. It achieves the following results on the evaluation set:

• Loss: 0.6396
• Rewards/chosen: -0.0338
• Rewards/rejected: -0.1547
• Rewards/accuracies: 0.6260
• Rewards/margins: 0.1209
• Logps/rejected: -282.4074
• Logps/chosen: -296.5363
• Logits/rejected: -2.1948
• Logits/chosen: -2.2954

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: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• total_eval_batch_size: 8
• 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	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.548	0.61	100	0.6396	-0.0338	-0.1547	0.6260	0.1209	-282.4074	-296.5363	-2.1948	-2.2954

Framework versions

• PEFT 0.7.1
• Transformers 4.36.2
• Pytorch 2.3.0+cu121
• Datasets 2.14.6
• Tokenizers 0.15.2