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

YYYYYYibo/nash_ave_pi_with_golden_iter_3

nash_ave_pi_with_golden_iter_3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

YYYYYYibo/
nash_ave_pi_with_golden_iter_3