This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.3298
Rewards/chosen: -0.1126
Rewards/rejected: -0.1126
Rewards/accuracies: 0.0
Rewards/margins: 0.0
Logps/rejected: -1.1264
Logps/chosen: -1.1264
Logits/rejected: 4.2177
Logits/chosen: 4.2177
Nll Loss: 1.2605
Log Odds Ratio: -0.6931
Log Odds Chosen: 0.0

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: 8e-06
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Nll Loss	Log Odds Ratio
3.4409	0.24	3	1.3298	-0.1126	-0.1126	-1.1264	-1.1264	4.2177	4.2177	1.2605	-0.6931
2.909	0.48	6	1.3298	-0.1126	-0.1126	-1.1264	-1.1264	4.2177	4.2177	1.2605	-0.6931
2.633	0.72	9	1.3298	-0.1126	-0.1126	-1.1264	-1.1264	4.2177	4.2177	1.2605	-0.6931
3.3955	0.96	12	1.3298	-0.1126	-0.1126	-1.1264	-1.1264	4.2177	4.2177	1.2605	-0.6931

Framework versions

PEFT 0.11.1
Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

vishal1829/orpo-phi

orpo-phi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vishal1829/
orpo-phi