This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:

Loss: 0.6096
Rewards/chosen: -1.0852
Rewards/rejected: -1.4834
Rewards/accuracies: 0.6976
Rewards/margins: 0.3982
Logps/rejected: -434.2651
Logps/chosen: -403.4777
Logits/rejected: 1.6861
Logits/chosen: 1.6753

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: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 128
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	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.62	0.8549	400	0.6104	-1.0659	-1.4533	0.6976	0.3875	-433.6641	-403.0910	1.6821	1.6709

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Ejafa/phi-3-mini-128k-instruct-dpo-lr-5e-07

Description

Authors

phi-3-mini-128k-instruct-dpo-lr-5e-07

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Ejafa/
phi-3-mini-128k-instruct-dpo-lr-5e-07